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Q3118061 Inglês
How online photos and videos alter the way you think



The images we are exposed to on social media and internet websites have a surprising influence on the way we view the world.


Every day we are bombarded with digital images. They appear on our social media feeds, in our search results and the websites we browse. People send them to us via messaging apps or over email. By the end of today, billions more will have been uploaded and shared online.


With the average user spending 6 hours and 40 minutes per day on the internet, according to one report, these images make up a significant portion of our everyday visual input.


And, recent research indicates that they may even be influencing our perceptions.


One study published earlier this year analysed images on Google,Wikipedia and the Internet Movie Database (IMBD), specifically looking at what genders predominated when they searched for different occupations − such as "farmer", "chief executive officer" or "TV reporter". The findings were stark. Although women were underrepresented overall, gender stereotypes were strong. Categories like "plumber", "developer", "investment banker" and "heart surgeon" were far more likely to be male. "Housekeeper", "nurse practitioner", "cheerleader" and "ballet dancer" tended to be female.


So far, so unsurprising. Anecdotally, I found the same phenomenon myself in 2019, when I was trying to find gender-balanced images for this website. Searching on Getty Creative, one of our main stock photo sites, I had found that photographs of male doctors outstripped female doctors by three to one − even though in the US, for example, physicians under 44 at the time were more likely to be female than male. This depiction of medical professionals were only part of the problem. There were twice as many options for photos of women with babies, or for that matter, of women with salads, as of men.


The more biased images AI models themselves spit out, the more we see; the more we see, the more implicitly biased we become ourselves


The latest study, however, took this a step further. Rather than just showing the extent of gender bias in online imagery, the researchers tested whether exposure to these images had any impact on people's own biases. In the experiment, 423 US participants used Google to search for different occupations. Two groups searched by text, using either Google or Google News; another group used Google Images, instead. (A control group also used Google, but to search for categories unrelated to occupations, like "apple" and "guitar"). Then all participants were given an "implicit association test", which measures implicit biases.


Compared to Googling text-based descriptions of occupations, the participants who used Google Images and received visual representations in response showed much higher rates of implicit gender bias after the experiment − both immediately after and three days later.


"The rise of images in popular internet culture may come at a critical social cost," the researchers write. "Our findings are especially alarming given that image-based social media platforms such as Instagram, Snapchat and TikTok are surging in popularity, accelerating the mass production and circulation of images. In parallel, popular search engines such as Google are increasingly incorporating images into their core functionality, for example, by including images as a default part of text-based searches."


There's another growing problem, too: how the images already circulating online are informing and shaping AI models. Earlier this year, I experimented with this myself. I asked ChatGPT to create images for me of dozens of various professionals: doctor, lawyer, scientist, comedian, poet, teacher, customer service representative, nutritionist, thought leader, CEO, expert. Except for two or three results − dental hygienist, nurse and housekeeper − it delivered, again and again, a man. And not just a man, but a slim white man around his 30s with a crop of flowing brown hair.


In a later attempt, trying to get away from career bias, I asked ChatGPT to come up with different sorts of people for me: someone "smart", someone "successful", someone watching an opera, someone watching the show Love Is Blind, someone who quit their job to take care of the kids. Once again, over and over, I got the white guy with the lustrous hair.


Obviously, models like ChatGPT are learning based on the imagery that already exists. But, once again, this may perpetuate a vicious cycle: the more biased images AI models themselves spit out, the more we see; the more we see, the more implicitly biased we become ourselves. And the more biased we become, the more we create and upload our own biased imagery.


So what can be done? A good deal of responsibility lies with the tech and AI companies. But even when their intentions are good, there doesn't seem to be an easy fix. In its attempt to correct for racial, gender and other biases, for example, Google's AI tool Gemini sometimes overcorrected − one image it generated of the US Founding Fathers included a black man, for example, while an image of German soldiers from World War Two featured a black man and an Asian woman.


In the meantime, we need to take control of shaping our digital visual world ourselves.


While it seems obvious, the fact that we can − to a certain extent − curate our social media feeds often goes overlooked. Seeking out accounts and influencers who are of different ethnic and racial backgrounds, or photographers from different parts of the woresults we get by altering the way we phrase the initial query.


The most effective strategy of all might be reclaiming our time. In the eponymous "digital detox plan" of art entrepreneur Marine Tanguy's book The Visual Detox: How to Consume Media Without Letting It Consume You, for example, there are no surprises, but some good, solid reminders − such as putting limits on when you look at a screen or your phone, deleting apps you aren't using, and spending time outside without technology.


I became aware recently that even my several-year-old phone has a timer you can switch on for various apps, choosing whatever time period per day you'd like. While I can't say that I've always heeded its warning when I hit my limit, it's helped me become much more aware of, and cut down on, my social media usage. As we have covered before, putting your phone in another room entirely seems to keep even the thought of checking it at bay.


Above all else, however, it may be awareness that is key. We don't often think about our visual consumption or consider how often we're surrounded by images that have been deliberately created and served to us, often to persuade us to purchase something.


Nor do we think about just how strange and new a phenomenon that is. For the vast majority of human evolutionary history − some 99% of the time we have been around − we wouldn't have seen many images within our own natural environment at all, save some cave paintings or handmade sculptures. While, in Europe, the Renaissance ushered in a new era of image production − which saw the rise of art markets and of artworks made for popular consumption, like printmaking − people still wouldn't have seen anywhere near the number of man-made images that we see today.


In the more than 100,000 generations since the Homo branch of the evolutionary tree emerged, we have evolved to spend far more time looking at the world (and people) around us than at images, never mind images on a screen. Perhaps, it seems, there is an argument for trying to incorporate more of that time away from our screens into our everyday lives today. 


https://www.bbc.com/future/article/20241101-how-online-photos-and-vid eos-alter-the-way-you-think 
What can be inferred about the impact of social media images on viewers, according to the article?
Alternativas
Q3118062 Inglês
How online photos and videos alter the way you think



The images we are exposed to on social media and internet websites have a surprising influence on the way we view the world.


Every day we are bombarded with digital images. They appear on our social media feeds, in our search results and the websites we browse. People send them to us via messaging apps or over email. By the end of today, billions more will have been uploaded and shared online.


With the average user spending 6 hours and 40 minutes per day on the internet, according to one report, these images make up a significant portion of our everyday visual input.


And, recent research indicates that they may even be influencing our perceptions.


One study published earlier this year analysed images on Google,Wikipedia and the Internet Movie Database (IMBD), specifically looking at what genders predominated when they searched for different occupations − such as "farmer", "chief executive officer" or "TV reporter". The findings were stark. Although women were underrepresented overall, gender stereotypes were strong. Categories like "plumber", "developer", "investment banker" and "heart surgeon" were far more likely to be male. "Housekeeper", "nurse practitioner", "cheerleader" and "ballet dancer" tended to be female.


So far, so unsurprising. Anecdotally, I found the same phenomenon myself in 2019, when I was trying to find gender-balanced images for this website. Searching on Getty Creative, one of our main stock photo sites, I had found that photographs of male doctors outstripped female doctors by three to one − even though in the US, for example, physicians under 44 at the time were more likely to be female than male. This depiction of medical professionals were only part of the problem. There were twice as many options for photos of women with babies, or for that matter, of women with salads, as of men.


The more biased images AI models themselves spit out, the more we see; the more we see, the more implicitly biased we become ourselves


The latest study, however, took this a step further. Rather than just showing the extent of gender bias in online imagery, the researchers tested whether exposure to these images had any impact on people's own biases. In the experiment, 423 US participants used Google to search for different occupations. Two groups searched by text, using either Google or Google News; another group used Google Images, instead. (A control group also used Google, but to search for categories unrelated to occupations, like "apple" and "guitar"). Then all participants were given an "implicit association test", which measures implicit biases.


Compared to Googling text-based descriptions of occupations, the participants who used Google Images and received visual representations in response showed much higher rates of implicit gender bias after the experiment − both immediately after and three days later.


"The rise of images in popular internet culture may come at a critical social cost," the researchers write. "Our findings are especially alarming given that image-based social media platforms such as Instagram, Snapchat and TikTok are surging in popularity, accelerating the mass production and circulation of images. In parallel, popular search engines such as Google are increasingly incorporating images into their core functionality, for example, by including images as a default part of text-based searches."


There's another growing problem, too: how the images already circulating online are informing and shaping AI models. Earlier this year, I experimented with this myself. I asked ChatGPT to create images for me of dozens of various professionals: doctor, lawyer, scientist, comedian, poet, teacher, customer service representative, nutritionist, thought leader, CEO, expert. Except for two or three results − dental hygienist, nurse and housekeeper − it delivered, again and again, a man. And not just a man, but a slim white man around his 30s with a crop of flowing brown hair.


In a later attempt, trying to get away from career bias, I asked ChatGPT to come up with different sorts of people for me: someone "smart", someone "successful", someone watching an opera, someone watching the show Love Is Blind, someone who quit their job to take care of the kids. Once again, over and over, I got the white guy with the lustrous hair.


Obviously, models like ChatGPT are learning based on the imagery that already exists. But, once again, this may perpetuate a vicious cycle: the more biased images AI models themselves spit out, the more we see; the more we see, the more implicitly biased we become ourselves. And the more biased we become, the more we create and upload our own biased imagery.


So what can be done? A good deal of responsibility lies with the tech and AI companies. But even when their intentions are good, there doesn't seem to be an easy fix. In its attempt to correct for racial, gender and other biases, for example, Google's AI tool Gemini sometimes overcorrected − one image it generated of the US Founding Fathers included a black man, for example, while an image of German soldiers from World War Two featured a black man and an Asian woman.


In the meantime, we need to take control of shaping our digital visual world ourselves.


While it seems obvious, the fact that we can − to a certain extent − curate our social media feeds often goes overlooked. Seeking out accounts and influencers who are of different ethnic and racial backgrounds, or photographers from different parts of the woresults we get by altering the way we phrase the initial query.


The most effective strategy of all might be reclaiming our time. In the eponymous "digital detox plan" of art entrepreneur Marine Tanguy's book The Visual Detox: How to Consume Media Without Letting It Consume You, for example, there are no surprises, but some good, solid reminders − such as putting limits on when you look at a screen or your phone, deleting apps you aren't using, and spending time outside without technology.


I became aware recently that even my several-year-old phone has a timer you can switch on for various apps, choosing whatever time period per day you'd like. While I can't say that I've always heeded its warning when I hit my limit, it's helped me become much more aware of, and cut down on, my social media usage. As we have covered before, putting your phone in another room entirely seems to keep even the thought of checking it at bay.


Above all else, however, it may be awareness that is key. We don't often think about our visual consumption or consider how often we're surrounded by images that have been deliberately created and served to us, often to persuade us to purchase something.


Nor do we think about just how strange and new a phenomenon that is. For the vast majority of human evolutionary history − some 99% of the time we have been around − we wouldn't have seen many images within our own natural environment at all, save some cave paintings or handmade sculptures. While, in Europe, the Renaissance ushered in a new era of image production − which saw the rise of art markets and of artworks made for popular consumption, like printmaking − people still wouldn't have seen anywhere near the number of man-made images that we see today.


In the more than 100,000 generations since the Homo branch of the evolutionary tree emerged, we have evolved to spend far more time looking at the world (and people) around us than at images, never mind images on a screen. Perhaps, it seems, there is an argument for trying to incorporate more of that time away from our screens into our everyday lives today. 


https://www.bbc.com/future/article/20241101-how-online-photos-and-vid eos-alter-the-way-you-think 
According to the author, what role does "awareness" play in managing the influence of images? 
Alternativas
Q3118063 Inglês
How online photos and videos alter the way you think



The images we are exposed to on social media and internet websites have a surprising influence on the way we view the world.


Every day we are bombarded with digital images. They appear on our social media feeds, in our search results and the websites we browse. People send them to us via messaging apps or over email. By the end of today, billions more will have been uploaded and shared online.


With the average user spending 6 hours and 40 minutes per day on the internet, according to one report, these images make up a significant portion of our everyday visual input.


And, recent research indicates that they may even be influencing our perceptions.


One study published earlier this year analysed images on Google,Wikipedia and the Internet Movie Database (IMBD), specifically looking at what genders predominated when they searched for different occupations − such as "farmer", "chief executive officer" or "TV reporter". The findings were stark. Although women were underrepresented overall, gender stereotypes were strong. Categories like "plumber", "developer", "investment banker" and "heart surgeon" were far more likely to be male. "Housekeeper", "nurse practitioner", "cheerleader" and "ballet dancer" tended to be female.


So far, so unsurprising. Anecdotally, I found the same phenomenon myself in 2019, when I was trying to find gender-balanced images for this website. Searching on Getty Creative, one of our main stock photo sites, I had found that photographs of male doctors outstripped female doctors by three to one − even though in the US, for example, physicians under 44 at the time were more likely to be female than male. This depiction of medical professionals were only part of the problem. There were twice as many options for photos of women with babies, or for that matter, of women with salads, as of men.


The more biased images AI models themselves spit out, the more we see; the more we see, the more implicitly biased we become ourselves


The latest study, however, took this a step further. Rather than just showing the extent of gender bias in online imagery, the researchers tested whether exposure to these images had any impact on people's own biases. In the experiment, 423 US participants used Google to search for different occupations. Two groups searched by text, using either Google or Google News; another group used Google Images, instead. (A control group also used Google, but to search for categories unrelated to occupations, like "apple" and "guitar"). Then all participants were given an "implicit association test", which measures implicit biases.


Compared to Googling text-based descriptions of occupations, the participants who used Google Images and received visual representations in response showed much higher rates of implicit gender bias after the experiment − both immediately after and three days later.


"The rise of images in popular internet culture may come at a critical social cost," the researchers write. "Our findings are especially alarming given that image-based social media platforms such as Instagram, Snapchat and TikTok are surging in popularity, accelerating the mass production and circulation of images. In parallel, popular search engines such as Google are increasingly incorporating images into their core functionality, for example, by including images as a default part of text-based searches."


There's another growing problem, too: how the images already circulating online are informing and shaping AI models. Earlier this year, I experimented with this myself. I asked ChatGPT to create images for me of dozens of various professionals: doctor, lawyer, scientist, comedian, poet, teacher, customer service representative, nutritionist, thought leader, CEO, expert. Except for two or three results − dental hygienist, nurse and housekeeper − it delivered, again and again, a man. And not just a man, but a slim white man around his 30s with a crop of flowing brown hair.


In a later attempt, trying to get away from career bias, I asked ChatGPT to come up with different sorts of people for me: someone "smart", someone "successful", someone watching an opera, someone watching the show Love Is Blind, someone who quit their job to take care of the kids. Once again, over and over, I got the white guy with the lustrous hair.


Obviously, models like ChatGPT are learning based on the imagery that already exists. But, once again, this may perpetuate a vicious cycle: the more biased images AI models themselves spit out, the more we see; the more we see, the more implicitly biased we become ourselves. And the more biased we become, the more we create and upload our own biased imagery.


So what can be done? A good deal of responsibility lies with the tech and AI companies. But even when their intentions are good, there doesn't seem to be an easy fix. In its attempt to correct for racial, gender and other biases, for example, Google's AI tool Gemini sometimes overcorrected − one image it generated of the US Founding Fathers included a black man, for example, while an image of German soldiers from World War Two featured a black man and an Asian woman.


In the meantime, we need to take control of shaping our digital visual world ourselves.


While it seems obvious, the fact that we can − to a certain extent − curate our social media feeds often goes overlooked. Seeking out accounts and influencers who are of different ethnic and racial backgrounds, or photographers from different parts of the woresults we get by altering the way we phrase the initial query.


The most effective strategy of all might be reclaiming our time. In the eponymous "digital detox plan" of art entrepreneur Marine Tanguy's book The Visual Detox: How to Consume Media Without Letting It Consume You, for example, there are no surprises, but some good, solid reminders − such as putting limits on when you look at a screen or your phone, deleting apps you aren't using, and spending time outside without technology.


I became aware recently that even my several-year-old phone has a timer you can switch on for various apps, choosing whatever time period per day you'd like. While I can't say that I've always heeded its warning when I hit my limit, it's helped me become much more aware of, and cut down on, my social media usage. As we have covered before, putting your phone in another room entirely seems to keep even the thought of checking it at bay.


Above all else, however, it may be awareness that is key. We don't often think about our visual consumption or consider how often we're surrounded by images that have been deliberately created and served to us, often to persuade us to purchase something.


Nor do we think about just how strange and new a phenomenon that is. For the vast majority of human evolutionary history − some 99% of the time we have been around − we wouldn't have seen many images within our own natural environment at all, save some cave paintings or handmade sculptures. While, in Europe, the Renaissance ushered in a new era of image production − which saw the rise of art markets and of artworks made for popular consumption, like printmaking − people still wouldn't have seen anywhere near the number of man-made images that we see today.


In the more than 100,000 generations since the Homo branch of the evolutionary tree emerged, we have evolved to spend far more time looking at the world (and people) around us than at images, never mind images on a screen. Perhaps, it seems, there is an argument for trying to incorporate more of that time away from our screens into our everyday lives today. 


https://www.bbc.com/future/article/20241101-how-online-photos-and-vid eos-alter-the-way-you-think 
 In the sentence "The more biased images AI models themselves spit out, the more we see; the more we see, the more implicitly biased we become ourselves," the author uses this structure to emphasize:
Alternativas
Q3118064 Inglês
How online photos and videos alter the way you think



The images we are exposed to on social media and internet websites have a surprising influence on the way we view the world.


Every day we are bombarded with digital images. They appear on our social media feeds, in our search results and the websites we browse. People send them to us via messaging apps or over email. By the end of today, billions more will have been uploaded and shared online.


With the average user spending 6 hours and 40 minutes per day on the internet, according to one report, these images make up a significant portion of our everyday visual input.


And, recent research indicates that they may even be influencing our perceptions.


One study published earlier this year analysed images on Google,Wikipedia and the Internet Movie Database (IMBD), specifically looking at what genders predominated when they searched for different occupations − such as "farmer", "chief executive officer" or "TV reporter". The findings were stark. Although women were underrepresented overall, gender stereotypes were strong. Categories like "plumber", "developer", "investment banker" and "heart surgeon" were far more likely to be male. "Housekeeper", "nurse practitioner", "cheerleader" and "ballet dancer" tended to be female.


So far, so unsurprising. Anecdotally, I found the same phenomenon myself in 2019, when I was trying to find gender-balanced images for this website. Searching on Getty Creative, one of our main stock photo sites, I had found that photographs of male doctors outstripped female doctors by three to one − even though in the US, for example, physicians under 44 at the time were more likely to be female than male. This depiction of medical professionals were only part of the problem. There were twice as many options for photos of women with babies, or for that matter, of women with salads, as of men.


The more biased images AI models themselves spit out, the more we see; the more we see, the more implicitly biased we become ourselves


The latest study, however, took this a step further. Rather than just showing the extent of gender bias in online imagery, the researchers tested whether exposure to these images had any impact on people's own biases. In the experiment, 423 US participants used Google to search for different occupations. Two groups searched by text, using either Google or Google News; another group used Google Images, instead. (A control group also used Google, but to search for categories unrelated to occupations, like "apple" and "guitar"). Then all participants were given an "implicit association test", which measures implicit biases.


Compared to Googling text-based descriptions of occupations, the participants who used Google Images and received visual representations in response showed much higher rates of implicit gender bias after the experiment − both immediately after and three days later.


"The rise of images in popular internet culture may come at a critical social cost," the researchers write. "Our findings are especially alarming given that image-based social media platforms such as Instagram, Snapchat and TikTok are surging in popularity, accelerating the mass production and circulation of images. In parallel, popular search engines such as Google are increasingly incorporating images into their core functionality, for example, by including images as a default part of text-based searches."


There's another growing problem, too: how the images already circulating online are informing and shaping AI models. Earlier this year, I experimented with this myself. I asked ChatGPT to create images for me of dozens of various professionals: doctor, lawyer, scientist, comedian, poet, teacher, customer service representative, nutritionist, thought leader, CEO, expert. Except for two or three results − dental hygienist, nurse and housekeeper − it delivered, again and again, a man. And not just a man, but a slim white man around his 30s with a crop of flowing brown hair.


In a later attempt, trying to get away from career bias, I asked ChatGPT to come up with different sorts of people for me: someone "smart", someone "successful", someone watching an opera, someone watching the show Love Is Blind, someone who quit their job to take care of the kids. Once again, over and over, I got the white guy with the lustrous hair.


Obviously, models like ChatGPT are learning based on the imagery that already exists. But, once again, this may perpetuate a vicious cycle: the more biased images AI models themselves spit out, the more we see; the more we see, the more implicitly biased we become ourselves. And the more biased we become, the more we create and upload our own biased imagery.


So what can be done? A good deal of responsibility lies with the tech and AI companies. But even when their intentions are good, there doesn't seem to be an easy fix. In its attempt to correct for racial, gender and other biases, for example, Google's AI tool Gemini sometimes overcorrected − one image it generated of the US Founding Fathers included a black man, for example, while an image of German soldiers from World War Two featured a black man and an Asian woman.


In the meantime, we need to take control of shaping our digital visual world ourselves.


While it seems obvious, the fact that we can − to a certain extent − curate our social media feeds often goes overlooked. Seeking out accounts and influencers who are of different ethnic and racial backgrounds, or photographers from different parts of the woresults we get by altering the way we phrase the initial query.


The most effective strategy of all might be reclaiming our time. In the eponymous "digital detox plan" of art entrepreneur Marine Tanguy's book The Visual Detox: How to Consume Media Without Letting It Consume You, for example, there are no surprises, but some good, solid reminders − such as putting limits on when you look at a screen or your phone, deleting apps you aren't using, and spending time outside without technology.


I became aware recently that even my several-year-old phone has a timer you can switch on for various apps, choosing whatever time period per day you'd like. While I can't say that I've always heeded its warning when I hit my limit, it's helped me become much more aware of, and cut down on, my social media usage. As we have covered before, putting your phone in another room entirely seems to keep even the thought of checking it at bay.


Above all else, however, it may be awareness that is key. We don't often think about our visual consumption or consider how often we're surrounded by images that have been deliberately created and served to us, often to persuade us to purchase something.


Nor do we think about just how strange and new a phenomenon that is. For the vast majority of human evolutionary history − some 99% of the time we have been around − we wouldn't have seen many images within our own natural environment at all, save some cave paintings or handmade sculptures. While, in Europe, the Renaissance ushered in a new era of image production − which saw the rise of art markets and of artworks made for popular consumption, like printmaking − people still wouldn't have seen anywhere near the number of man-made images that we see today.


In the more than 100,000 generations since the Homo branch of the evolutionary tree emerged, we have evolved to spend far more time looking at the world (and people) around us than at images, never mind images on a screen. Perhaps, it seems, there is an argument for trying to incorporate more of that time away from our screens into our everyday lives today. 


https://www.bbc.com/future/article/20241101-how-online-photos-and-vid eos-alter-the-way-you-think 
What reasoning does the author provide for suggesting a "digital detox" as part of managing the influence of online images? 
Alternativas
Q3118065 Inglês
How online photos and videos alter the way you think



The images we are exposed to on social media and internet websites have a surprising influence on the way we view the world.


Every day we are bombarded with digital images. They appear on our social media feeds, in our search results and the websites we browse. People send them to us via messaging apps or over email. By the end of today, billions more will have been uploaded and shared online.


With the average user spending 6 hours and 40 minutes per day on the internet, according to one report, these images make up a significant portion of our everyday visual input.


And, recent research indicates that they may even be influencing our perceptions.


One study published earlier this year analysed images on Google,Wikipedia and the Internet Movie Database (IMBD), specifically looking at what genders predominated when they searched for different occupations − such as "farmer", "chief executive officer" or "TV reporter". The findings were stark. Although women were underrepresented overall, gender stereotypes were strong. Categories like "plumber", "developer", "investment banker" and "heart surgeon" were far more likely to be male. "Housekeeper", "nurse practitioner", "cheerleader" and "ballet dancer" tended to be female.


So far, so unsurprising. Anecdotally, I found the same phenomenon myself in 2019, when I was trying to find gender-balanced images for this website. Searching on Getty Creative, one of our main stock photo sites, I had found that photographs of male doctors outstripped female doctors by three to one − even though in the US, for example, physicians under 44 at the time were more likely to be female than male. This depiction of medical professionals were only part of the problem. There were twice as many options for photos of women with babies, or for that matter, of women with salads, as of men.


The more biased images AI models themselves spit out, the more we see; the more we see, the more implicitly biased we become ourselves


The latest study, however, took this a step further. Rather than just showing the extent of gender bias in online imagery, the researchers tested whether exposure to these images had any impact on people's own biases. In the experiment, 423 US participants used Google to search for different occupations. Two groups searched by text, using either Google or Google News; another group used Google Images, instead. (A control group also used Google, but to search for categories unrelated to occupations, like "apple" and "guitar"). Then all participants were given an "implicit association test", which measures implicit biases.


Compared to Googling text-based descriptions of occupations, the participants who used Google Images and received visual representations in response showed much higher rates of implicit gender bias after the experiment − both immediately after and three days later.


"The rise of images in popular internet culture may come at a critical social cost," the researchers write. "Our findings are especially alarming given that image-based social media platforms such as Instagram, Snapchat and TikTok are surging in popularity, accelerating the mass production and circulation of images. In parallel, popular search engines such as Google are increasingly incorporating images into their core functionality, for example, by including images as a default part of text-based searches."


There's another growing problem, too: how the images already circulating online are informing and shaping AI models. Earlier this year, I experimented with this myself. I asked ChatGPT to create images for me of dozens of various professionals: doctor, lawyer, scientist, comedian, poet, teacher, customer service representative, nutritionist, thought leader, CEO, expert. Except for two or three results − dental hygienist, nurse and housekeeper − it delivered, again and again, a man. And not just a man, but a slim white man around his 30s with a crop of flowing brown hair.


In a later attempt, trying to get away from career bias, I asked ChatGPT to come up with different sorts of people for me: someone "smart", someone "successful", someone watching an opera, someone watching the show Love Is Blind, someone who quit their job to take care of the kids. Once again, over and over, I got the white guy with the lustrous hair.


Obviously, models like ChatGPT are learning based on the imagery that already exists. But, once again, this may perpetuate a vicious cycle: the more biased images AI models themselves spit out, the more we see; the more we see, the more implicitly biased we become ourselves. And the more biased we become, the more we create and upload our own biased imagery.


So what can be done? A good deal of responsibility lies with the tech and AI companies. But even when their intentions are good, there doesn't seem to be an easy fix. In its attempt to correct for racial, gender and other biases, for example, Google's AI tool Gemini sometimes overcorrected − one image it generated of the US Founding Fathers included a black man, for example, while an image of German soldiers from World War Two featured a black man and an Asian woman.


In the meantime, we need to take control of shaping our digital visual world ourselves.


While it seems obvious, the fact that we can − to a certain extent − curate our social media feeds often goes overlooked. Seeking out accounts and influencers who are of different ethnic and racial backgrounds, or photographers from different parts of the woresults we get by altering the way we phrase the initial query.


The most effective strategy of all might be reclaiming our time. In the eponymous "digital detox plan" of art entrepreneur Marine Tanguy's book The Visual Detox: How to Consume Media Without Letting It Consume You, for example, there are no surprises, but some good, solid reminders − such as putting limits on when you look at a screen or your phone, deleting apps you aren't using, and spending time outside without technology.


I became aware recently that even my several-year-old phone has a timer you can switch on for various apps, choosing whatever time period per day you'd like. While I can't say that I've always heeded its warning when I hit my limit, it's helped me become much more aware of, and cut down on, my social media usage. As we have covered before, putting your phone in another room entirely seems to keep even the thought of checking it at bay.


Above all else, however, it may be awareness that is key. We don't often think about our visual consumption or consider how often we're surrounded by images that have been deliberately created and served to us, often to persuade us to purchase something.


Nor do we think about just how strange and new a phenomenon that is. For the vast majority of human evolutionary history − some 99% of the time we have been around − we wouldn't have seen many images within our own natural environment at all, save some cave paintings or handmade sculptures. While, in Europe, the Renaissance ushered in a new era of image production − which saw the rise of art markets and of artworks made for popular consumption, like printmaking − people still wouldn't have seen anywhere near the number of man-made images that we see today.


In the more than 100,000 generations since the Homo branch of the evolutionary tree emerged, we have evolved to spend far more time looking at the world (and people) around us than at images, never mind images on a screen. Perhaps, it seems, there is an argument for trying to incorporate more of that time away from our screens into our everyday lives today. 


https://www.bbc.com/future/article/20241101-how-online-photos-and-vid eos-alter-the-way-you-think 
In the context of the article, what does the phrase "curate our social media feeds" imply?
Alternativas
Q3118066 Inglês
In formative assessment, what is the primary purpose of providing feedback to students during the learning process?
Alternativas
Q3118067 Inglês
A teacher is planning a reading activity designed to enhance students' critical reading skills in a high school English class. The chosen text discusses a controversial issue. What approach would best facilitate students' development of these skills according to modern communicative and critical pedagogy principles? 
Alternativas
Q3118068 Inglês
Regarding the role of school in the 21st century, select the CORRECT alternative. 
Alternativas
Q3118069 Inglês
When designing a lesson plan focused on developing speaking skills in an intermediate-level English class, which of the following would be the most effective strategy to encourage student participation and language use?
Alternativas
Q3118070 Inglês
 In the context of Vygotsky's theory of the Zone of Proximal Development (ZPD), which teaching strategy would be most effective in supporting a student's learning progress?
Alternativas
Q3118071 Inglês
Which of the following best differentiates the Total Physical Response (TPR) approach from the Audiolingual method in teaching English as a foreign language?
Alternativas
Q3118072 Inglês
In which sentence is the use of the subjunctive mood correctly applied? 
Alternativas
Q3118073 Inglês
In the following sentence, identify the grammatical function of the word "that" and choose the option that best explains its role: "It was the kind of movie that left the audience speechless."
Alternativas
Q3118074 Inglês
Identify the sentence where the choice of phrasal verb conveys the closest meaning to "resolve an issue": 
Alternativas
Q3118075 Português
Assinale a alternativa que possua um vício de linguagem conhecido como solecismo:
Alternativas
Q3118076 Português
Leia com atenção a afirmativa abaixo:

Para a viagem levaria somente o que iria utilizar: bermudas e chinelos.

Qual é a função que os termos destacados desempenham na oração? 
Alternativas
Q3118077 Português
Leia com atenção as afirmativas abaixo:

I.Tenho esperança de que tudo se resolva logo.
II.Só tenho um desejo: que todos sejam felizes.
III.É importante que você estude todos os dias.
IV.Convém que todos compareçam à reunião.
V.Ele tinha certeza de que conseguiria o emprego.

Em quais das afirmativas lidas há o emprego de uma oração subordinada substantiva subjetiva?
Alternativas
Q3118078 Legislação dos Municípios do Estado de Santa Catarina
De acordo com a Lei Orgânica Municipal de Anchieta, é da competência comum do Município, do Estado e da União, EXCETO: 
Alternativas
Q3118079 Conhecimentos Gerais
Sobre os desafios da educação no Brasil, há uma busca crescente por inovações que melhorem a qualidade do ensino, especialmente diante das desigualdades regionais. Qual das alternativas a seguir demonstra corretamente uma tendência recente em políticas educacionais voltadas ao enfrentamento dessas desigualdades e suas potenciais limitações? 
Alternativas
Q3118080 Legislação dos Municípios do Estado de Santa Catarina
Segundo a Lei Orgânica Municipal de Anchieta, o Prefeito perderá o mandato por extinção, ou será declarada pela Mesa da Câmara Municipal, mediante registro em ata, quando, EXCETO:
Alternativas
Respostas
1: B
2: C
3: C
4: A
5: C
6: A
7: C
8: B
9: A
10: A
11: C
12: B
13: A
14: B
15: B
16: B
17: A
18: B
19: B
20: D