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AI for Educators Series: Part Two: Evaluating AI-Generated Content

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AI for Educators Series: A Concise Series on Practical AI Tools Simple and Actionable Insights Featured Article Part Two: Evaluating AI-Generated Content Teaching educators how to critically assess the information and content produced by AI, including checking for accuracy, bias, and appropriateness

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Is It Real? Using Reverse Image Search | Common Sense Education | PBS LearningMedia

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How do you know if an online image is real or not? This video from Common Sense Education provides useful guidance on using reverse image search on Google. This resource is part of the News and Media Literacy Collection.

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Teaching Students How to Identify Credible Sources

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Teachers can guide students toward a clear understanding of the factors that make a particular source of information reliable or not.

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We have an alert about fake photos making the rounds on social media and a news report, this teen "Vogue" image of March for our lives student Emma Gonzalez ripping up a gun target was doctored to look like she was rip up the constitution. Rebecca Jarvis is back with it. It's kind of hard. It is and it's become so prevalent, robin. These are all over the internet. These doctored photos have become so prevalent they flooded the internet. Many going viral and make it all the way around the world before anyone realizes it's a fake which is why you have to know how to tell the difference between the original and a hoax. This photo of parkland activist Emma Gonzalez part of a cover from "Teen vogue's" new digital cover dedicated to gun violence. We had target paper from the prop stylist and she ripped it. It was a metaphor for the fact that these kids don't want to be targetses for shooters and for violence anymore. Reporter: But just as the cover photo began to spread, a fake gif was cited showing her not tearing up the gun range target but instead making it look like she was tearing up the constitution. Here is our cover and you can see clearly that she's tearing a target paper and on the left, you can see this grainy video, another sign it's fake and also you can see the text of the constitution sort of shakes when she started to rip it. Reporter: The fake image going viral. Turbocharged on social media after it was posted by gag which bills itself as the free speech social media on Twitter and referred to it as a satirical meme. Once misinformation is out there it's out there and it's far easier to spread lies than to correct them. Reporter: The technology to manipulate videos and photos more accessible than ever. Now there is software that can be purchased and done at home and within a few days you can manufacture what someone says. In a video. So we are entering into dark times some tips. Follow the chain and see where that information first originated. Do a reverse Google search and trust your gut. If it seems unlikely, it probably is. And one area that's really become a target of these fake photos are natural disasters after hurricanes, tornadoes, major storms. We've seen a bunch of these hoax photos all over the internet. If you see a shark, for example, in a picture swimming down a main street, be skeptical. That photo is very likely a fake. I know. But there are times in the case of this young woman who is trying to do her best to bring about change and it being used against her like this, such challenging times right now. Are there ways to spot when it's a fake. We took a picture that I posted to my Instagram account a few days after "Good morning America." This is the real picture. No filter and then we had a producer doctor it. Now, this is the picture that's been doctored and there are a couple of telltale signs. First of all, look at these branches. You have duplicates that weren't in the original. The branches look identical. Then look at the was. It's warped here. Mismatching. No matching and often you see it with a brick wall where the bricks don't line up on the wall. Here's where you see things along the floor. It's also, you can see here these floorboards no longer match up. It's a little bit fuzzy here where the floorboards exist then finally look for shadows in those photos because here you can see there's a shadow. But here in the fixed hoax version, no shadow here anymore so these are the things to look for. It's not easy, robin. It's not easy at all. But can you look for these things and they will often show up in the hoax photos. Also, give people the benefit of the doubt. When you see something that you're like, could that reel be? Give them the benefit of the doubt. Use skepticism. And do research because you can do like you said the reverse Google and things like that. Maybe get to the bottom of it. It's important to be skeptical in these times. Yeah, all right, thank you, Rebecca, so much.

This transcript has been automatically generated and may not be 100% accurate.

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We have an alert about fake photos making the rounds on social media and a news report, this teen "Vogue" image of March for our lives student Emma Gonzalez ripping up a gun target was doctored to look like she was rip up the constitution. Rebecca Jarvis is back with it.

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Vocabulary

reliable [ri- lahy- uh-b uhl](adjective) trustworthy; containing true and legitimate information

[ih- evaluate val-yoo-eyt] (verb) to judge or determine the reliability of information

online [on- lahyn] (adjective) found on the internet

reasoning [ ree- zuh-ning] (noun) the act of thinking through

Series Overview

As technology advances and the social landscape shifts, it is crucial for students to become digitally literate citizens. In this series, elementary students will learn the ins and outs of media literacy, from choosing reliable sources and understanding online searches to navigating online security and participating in digital communities. More lessons in this series are listed under "Related Resources."

Lesson Overview

This lesson addresses the importance of locating and verifying reliable sources when working with online information. Students will compare and contrast different sources on the same topic and think about what makes one source more reliable than another. They will then work collaboratively to develop a checklist of questions for source evaluation.

Students will also zero in on the significance of evaluating sources for bias. They will learn to identify the author's or designer's purpose in online information and use this skill to search out biased viewpoints. Students will react to sources presented online and identify common reasoning errors in reactions to digital information.

Procedure

Compare and Contrast

1. Explain to your students that you are going to have them look at two to three different websites about school lunches and consider the information presented. Explain that all of these sites came from a basic search of the words "school lunch." Give them printouts or screenshots of two to three of the following webpages:

2. Give students 10 minutes to scan the information on the printouts or screenshots you have shown them.

3. Have students work in partnerships or small groups to complete the Choosing Reliable Sources Venn diagram worksheetcomparing and contrasting the sources they have reviewed. Where the circles don't overlap, students should write details that tell how the webpages are different. Where the circles overlap, they should write details that tell how the webpages are alike. Encourage students to think about the information conveyed through photographs and other images as well as text. If your students are unaccustomed to working with Venn diagrams, you can do this activity as a whole group.

If students need help finding similarities and differences, you can use the following questions to aid their work:

When was each page created or updated?

What is similar or different about the images on each page?

What is the main idea or reason behind each page?

What seems to be the author's purpose on each page?

Develop a Checklist

1. Bring your students together. Explain that different sources online present different information, even about the same topics. As students work with online information, they should think about which sources are the most reliable.

2. Provide students with a definition of the term reliable.Write "Our Reliability Checklist" on the board, and have students offer ideas for questions they might ask themselves when evaluating the reliability of a source. If your students have trouble getting started, you can model questions for them:

Who wrote this source?

What was the purpose of the author who wrote this source?

What other sources does this source reference?

Does this source say the same things as other sources?

Does this source echo what I know from personal experience?

3. You can keep this checklist posted in your classroom or type it up for students to put in notebooks or on their walls at home.

4. Have students answer the questions for the websites they reviewed and choose which of the two or three sources is most reliable. You can do this as a class or in small groups.

Kids React

1. Finally, perform an online image search for the words "school lunch," and project the results or create handouts with the images from the search results. Have students focus their attention on one image at a time. Ask them to make a face or display thumbs up, down or in the middle to convey their emotional reaction to the image. Chart their reactions.

2. As a class, discuss the assumptions they might have been making when reacting to these images. Some examples of assumptions are below:

All school lunches are disgusting.

All school lunches are nutritious.

Kids are usually smiling when they eat school lunch.

Kids only like junk food.

Schools are always racially diverse.

American kids are less healthy than kids in other countries.

3. Referring back to the chart of student reactions, have kids write in their notebooks or journals about some of the assumptions a person might find themselves making based on a simple online image search.
Alignment to Common Core State Standards
CCSS.ELA-Literacy.RI.4.2
Determine the main idea of a text and explain how it is supported by key details; summarize the text.

CCSS.ELA-Literacy.RI.4.7
Interpret information presented visually, orally, or quantitatively (e.g., in charts, graphs, diagrams, time lines, animations, or interactive elements on Web pages) and explain how the information contributes to an understanding of the text in which it appears.

CCSS.ELA-Literacy.RI.4.8
Explain how an author uses reasons and evidence to support particular points in a text.

CCSS.ELA-Literacy.RI.4.9
Integrate information from two texts on the same topic in order to write or speak about the subject knowledgeably.

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This lesson, part of the Digital Literacy series, addresses the importance of locating and verifying reliable sources when working with online information.

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"AI Ian" Shows You How Not to be Duped by AI Technology | Be MediaWise | PBS LearningMedia

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While cloning someone's voice can be entertaining, AI technology has become so good that you might actually think that President Joe Biden mocked people identifying as transgender or that Emma Watson really read Mein Kampf on Twitter. Students are being bombarded with synthetic images, AI-generated text and now voice-cloning.

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By Sierra Filucci | March 5, 2021

This just in! Breaking news! You don't want to miss THIS!

If you get your news online or from social media, this type of headline sounds very familiar. What's real? What's fake? What's satire? Now that anyone with access to a phone or computer can publish information online, it's getting harder to tell. But as more people go to Facebook, Snapchat, Twitter and other online sources for their news and information, it's even more crucial that all of us -- especially kids -- learn to decode what we read online. (Learn more about how kids get their news and how they feel about it in Common Sense Media's report, News and America's Kids: How Young People Perceive and Are Impacted by the News.)

When fake news, such as false claims about the coronavirus, has threatened people's safety, tech companies have joined forces to crack down on the misinformation super-spreaders. But ad-supported networks are in somewhat of a bind, since they get money when users click on these stories -- so the crazier the headline, the more money they make. Most kids and teens get their news from their feeds, so they need to learn how to view stories critically (and they should learn that skill anyway!). Even little kids can start to think about some key media-literacy questions. And as kids get older, parents can help kids become more sophisticated critical thinkers. (If your kid's school is tackling media-literacy issues, consider sharing this with their teachers.)

Here are a few basic questions to consider whenever you and your kids encounter a piece of media:

Who made this?

Who is the target audience?

Who paid for this? Or, who gets paid if you click on this?

Who might benefit or be harmed by this message?

What is left out of this message that might be important?

Is this credible (and what makes you think that)?

(Thanks to Project Look Sharp for these questions.)

Older kids especially might enjoy learning tricks to spot fake news. Here are a few things to watch for:

Look for unusual URLs or site names, including those that end with ".co" -- these are often trying to appear like legitimate news sites, but they aren't.

Look for signs of low quality, such as words in all caps, headlines with glaring grammatical errors, bold claims with no sources, and sensationalist images (women in bikinis are popular clickbait on fake news sites). These are clues that you should be skeptical of the source.

Check a site's "About Us" section. Find out who supports the site or who is associated with it. If this information doesn't exist -- and if the site requires that you register before you can learn anything about its backers -- you have to wonder why they aren't being transparent.

Check Snopes, Wikipedia, and Google before trusting or sharing news that seems too good (or bad) to be true.

Consider whether other credible, mainstream news outlets are reporting the same news. If they're not, it doesn't mean it's not true, but it does mean you should dig deeper.

Check your emotions. Clickbait and fake news strive for extreme reactions. If the news you're reading makes you really angry or super smug, it could be a sign that you're being played. Check multiple sources before trusting.

(Thanks to Professor Melissa Zimdars of Merrimack College for some of these tips.)

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How to Spot Fake News (and Teach Kids to Be Media-Savvy)

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Clickbait, hyper-partisan opinion, and completely false information are running wild across the internet. Advice from Common Sense Media editors.

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How high schools are teaching students to spot digital hoaxes

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Viral conspiracy theories and fake AI-generated images are now everywhere.

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Test Yourself: Which Faces Were Made by A.I.?

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People tend to overestimate their ability to spot digital fakes, researchers found.

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Not for Kids due to Profanity in the Name

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Not for Kids due to Profanity in the Name

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Which Face is Real?

Which Face Is Real? was developed by Jevin West and Carl Bergstrom from the University of Washingtion as part of the Calling Bullshit Project. It acts as a sort of game that anyone can play. Visitors to the site have a choice of two images, one of which is real and the other of which is a fake generated by StyleGAN.

The project was implemented by Jevin and Carl as a course that will teach its students how to identify misinformation.

Our aim in this course is to teach you how to think critically about the data and models that constitute evidence in the social and natural sciences.

The world is awash in bullshit. Politicians are unconstrained by facts. Science is conducted by press release. Higher education rewards bullshit over analytic thought. Startup culture elevates bullshit to high art. Advertisers wink conspiratorially and invite us to join them in seeing through all the bullshit - and take advantage of our lowered guard to bombard us with bullshit of the second order. The majority of administrative activity, whether in private business or the public sphere, seems to be little more than a sophisticated exercise in the combinatorial reassembly of bullshit.

We're sick of it. It's time to do something, and as educators, one constructive thing we know how to do is to teach people. So, the aim of this course is to help students navigate the bullshit-rich modern environment by identifying bullshit, seeing through it, and combating it with effective analysis and argument.

-Carl T. Bergstrom and Jevin West
Seattle, WA.

How do you tell the Difference?

The algorithm produces shiny blobs that look somewhat like water splotches on old photographic prints. These splotches can appear anywhere in the image, but often show up at the interface between the hair and the background.
Background problems

The background of the image can appear in a weird state such as blurriness or mishaped objects. This is due to the fact that the neural net is trained on the face and less emphasis is given to the background of the image.

Symmetry

At the moment, the generator is not able to produce realistic looking eyeglasses, however this may not be obvious at first. A common problem is asymmetry. Look at the frame structure; often the frame will take one style at the left and another at the right, or there will be a wayfarer-style ornament on one side but not on the other. Other times the frame will just be crooked or jagged. In addition, asymmetries in facial hair, different earrings in the left and right ear, and different forms of collar or fabric on the left and right side can be present.

Hair

Hair is known to be difficult for the algorithm to render properly. Disconnected strands, too straight, or too streaked will be common problems when generating hair.

Fluorescent bleed

Fluorescent colors can sometimes bleed into the hair or face from the background. People can sometimes mistake this for colored hair.

Teeth

Teeth are also hard to render and can come out as odd-shaped, asymmetric or for those that can identify teeth, sometimes 3 incisors can appear in the image.

Trying the algorithm

All the code for the StyleGAN have been open-sourced in the stylegan repository. It gives details on how you can run the styleGAN algorithm yourself.
However, there are a few barriers:

System Requirements

Training time

System Requirements

Both Linux and Windows are supported, but we strongly recommend Linux for performance and compatibility reasons.

64-bit Python 3.6 installation. We recommend Anaconda3 with numpy 1.14.3 or newer.

TensorFlow 1.10.0 or newer with GPU support.

One or more high-end NVIDIA GPUs with at least 11GB of DRAM. We recommend NVIDIA DGX-1 with 8 Tesla V100 GPUs.

NVIDIA driver 391.35 or newer, CUDA toolkit 9.0 or newer, cuDNN 7.3.1 or newer.

That type of compute and storage capacity is not common among individuals.

Training time

Below you will find NVIDIA's reported expected training times for default configuration of the train.py script (available in the stylegan repository) on a Tesla V100 GPU for the FFHQ dataset (available in the stylegan repository).

The time taken to properly train this algorithm is far beyond the patience of an everyday individual.

Behind the scenes

The science behind the app is thanks to a team at NVIDIA and their work on Generative Adversarial Networks. They created the StyleGAN. To learn a little more about this amazing technique, I have provided some resources and concise explanations below.

Generative Adversarial Network

For those wanting a refresher on GAN's, this playlist of tutorials on GAN's by Ahlad Kumar is quite helpful.

Generative Adversarial Networks first made the rounds in 2014 as an extension of generative models via an adversarial process in which we simultaneously train two models:

A generative model that captures the data distribution (training)

A discriminative model that estimates the probability that a sample came from the
training data rather than the generative model.

The goal of GAN's is to generate artificial/fake samples that are indistinguishable from authentic/real samples. A common example is generating artificial images that are indistinguishable from real photos of people. The human visual processing system would not be able to differentiate these images so easily as the images will look like real people at first. We will later see how this happens and how we can distinguish a photo of a real person and a photo generated by an algorithm.

StyleGAN

The algorithm behind this amazing app was the brainchild of Tero Karras, Samuli Laine and Timo Aila at NVIDIA and called it . The algorithm is based on earlier work by Ian Goodfellow and colleagues on General Adversarial Networks (GAN's). NVIDIA open sourced the code for their StyleGAN which uses GAN's in which two neural networks, one to generate indistinguishable artificial images while the other will attempt to distinguish between fake and real photographs.

But while we've learned to distrust user names and text more generally, pictures are different. You can't synthesize a picture out of nothing, we assume; a picture had to be of someone. Sure a scammer could appropriate someone else's picture, but doing so is a risky strategy in a world with google reverse search and so forth. So we tend to trust pictures. A business profile with a picture obviously belongs to someone. A match on a dating site may turn out to be 10 pounds heavier or 10 years older than when a picture was taken, but if there's a picture, the person obviously exists.

No longer. New adversarial machine learning algorithms allow people to rapidly generate synthetic 'photographs' of people who have never existed.

- Jevin West and Carl Bergstrom
Generative models have a limitation in which it's hard to control the characteristics such as facial features from photographs. NVIDIA's StyleGAN is a fix to this limitation. The model allows the user to tune hyper-parameters that can control for the differences in the photographs.
StyleGAN solves the variability of photos by adding styles to images at each convolution layer. These styles represent different features of a photos of a human, such as facial features, background color, hair, wrinkles etc. The algorithm generates new images starting from a low resolution (4x4) to a higher resolution (1024x1024). The model generates two images A and B and then combines them by taking low-level features from A and rest from B. At each level, different features (styles) are used to generate an image:

Coarse styles (resolution between 4 to 8) - pose, hair, face, shape

Middle styles (resolution between 16 to 32) - facial features, eyes

Fine styles (resolution between 64 to 1024)- color scheme

Properties of the style-based generator
Style mixing

The generator employs mixing regularization where a given percentage of images are generated using two random latent codes instead of one during training. When generating such an image, the user simply switches from one latent code to another (i.e. style mixing) at a randomly selected point in the synthesis network. In the below image we can see how the styles generated by one latent code (source) override a subset of the styles of another latent code (destination)

Stochastic Variation

Many aspects of a photograph are stochastic (i.e. random) such as wrinkles, hair placement, stubbles, freckles, pimples. The architecture of StyleGAN adds per-pixel noise after each convolution layer in order for images to show these variations as seen in real life. As seen in the below image, noise added by the generator only affects the stochastic aspects of the image and leaves the higher level styles as they are.

Separation of global effects from stochasticity

Changes to the style of the image will have global effects such as changing pose, gender, face etc. but the noise such as freckles, wrinkles, hair placement will only affect the stochastic variation. In StyleGAN, global effects such as pose, lighting or background style can be controlled coherently and the noise is added independently to each pixel and is thus ideally suited for controlling stochastic variation.

Helpful resources
Related:

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Which Face Is Real? was developed based on Generative Adversarial Networks as a web application in which users can select which image they believe is a true person and which was synthetically generated. The person in the synthetically generated photo does not exist.

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AI images and conspiracy theories are driving a push for media literacy education

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One of the nation’s best-known media literacy events for high school students is expanding as demand grows for skills to identify deepfake images and online conspiracy theories.

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The main annual MisinfoDay events are on the campuses of the University of Washington Seattle, Washington State University Pullman and WSU Vancouver. The events are t ypically hosted in March, and registration opens in the November/December of the previous year.

For those unable to attend MisinfoDay on university campuses, we offer new MisinfoDay lessons and activities for you to run your own MisinfoDay, together with other educators around the world!

Learn how to attend and/or participate in MisinfoDay March Events here.

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Learn more about our MisinfoDay educational program.

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Teaching Students How to Identify Credible Sources

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Teachers can guide students toward a clear understanding of the factors that make a particular source of information reliable or not.

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The News Literacy Project works with educators and journalists to give students the skills they need to discern fact from fiction and to know what to trust.

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Generate photo-realistic images from text using Stable Diffusion XL | getimg.ai

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We provide simple access to Stable Diffusion models, which enables generating photo-realistic images with given text input.

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Humans Are Biased. Generative AI Is Even Worse

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Text-to-image models amplify stereotypes about race and gender — here’s why that matters

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One day, Ammaar Reshi was playing around with a chatbot called ChatGPT. It's a computer program. It uses artificial intelligence (AI) to imitate thinking and writing. Reshi decided to use it to make a children's book. The chatbot helped Reshi come up with a story about a girl named Alice. Reshi made illustrations using another AI program, Midjourney. It translates words into images.

The book, Alice and Sparkle, was done in just a couple of days. "Anyone can use these [AI] tools," Reshi told TIME. "[They're] readily accessible. And not hard to use."

COURTESY AMMAAR RESHI

Reshi posted about the book on Twitter. Not everyone was pleased. Some people praised him for his ingenuity ingenuity creativity; inventiveness (noun) The students showed their ingenuity by writing a song for the teacher's birthday. . But artists were critical. They said the artwork was poor. (In one drawing, hands look like claws.) The way the art was made was a problem too.

COURTESY AMMAAR RESHI

Midjourney searches through millions of images on the Internet. It uses algorithms algorithm a set of instructions that tells a computer program how to accomplish a task (noun) The company used an algorithm to recommend its product online. to find patterns in those images and create new ones. Artists often upload their work online. Midjourney could be using their work without their permission.

"The main problem to me about AI is that it was trained off of artists' work," illustrator Adriane Tsai says. "It's our creations . . . that we did not consent to being used."

For Art's Sake

COURTESY AMMAAR RESHI

Many artists and writers are nervous about the future. Will people pay for their work if it can be done cheaper using AI?

Some companies are already choosing AI over human talent. The San Francisco Ballet used images made with Midjourney to promote its production of The Nutcracker. At a comedy club, an AI-powered robot told jokes. Abraham Josephine Riesman is a journalist. "It's deeply troubling to see people seeking cheap alternatives to actual human writing," she says.

Reshi says tech companies should protect artists and authors: "It's really important that the tech industry that's working on these tools involves [artists] in the process of creation."

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One day, Ammaar Reshi was playing around with a chatbot called ChatGPT. It's a computer program. It uses artificial intelligence (AI) to imitate thinking and writing. Reshi decided to use it to make a children's book. The chatbot helped Reshi come...

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Check out this minilesson: Evaluating Sources of Information

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Whether you are reading the news or working on a research project, you should use a critical eye. Evaluating sources helps you judge whether information is reliable and trustworthy or faulty and misleading. In today’s volatile media environment, those distinctions often blur, making it more difficult to discern credible sources from deceptive ones.

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Teaching Students How to Identify Credible Sources

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Teachers can guide students toward a clear understanding of the factors that make a particular source of information reliable or not.

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Text or images generated by AI tools have no human author, but they are trained on materials created by humans with human biases. Unlike humans, AI tools cannot reliably distinguish between biased material and unbiased material when using information to construct their responses.
What was the intended audience?
Generative AI tools can be used to generate content for any audience based on the user's prompt.
What is the intended purpose of the content? Was it created to inform, to make money, to entertain?
Generative AI tools can create convincing text and images that can be used to propagate many different ideas without being clear that the information or images could be false.
Where was it published? Was it in a scholarly publication, a website, or an organization page?
Generative AI has already been used to create content for websites and news outlets. Considering whether the source is scholarly, has a good reputation and a clear history of providing reliable information is useful for figuring out whether the information you find is useful or misleading.
Does it provide sources for the information?
Articles, news outlets, and websites that provide sources could be an indicator of reliability. Further assessing the sources by following the links and citations to verify the information will help confirm that the information you find is reliable.

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LibGuides: AI Tools and Resources: Generative AI Reliability and Authority

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Introduction to generative AI concepts and tools

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RAISE has developed a wide range of learning units for K12 AI Literacy that are available under Creative Commons licensing

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Introduce AI into your children’s lives.

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This is the second mini-lesson in a two-part series on the impact of generative AI tools such as ChatGPT and DALL-E on education.

Advisory

English & Language Arts

Social Studies

Propaganda

Democracy & Civic Engagement

Most teachers are willing to tackle the difficult topics, but we need the tools.

- Gabriela Calderon-Espinal, Bay Shore, NY

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Learning to Navigate Generative AI Content: Media Literacy Strategies

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This is the second mini-lesson in a two-part series on the impact of generative AI tools such as ChatGPT and DALL-E on education.

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Introduction

As technology continues to advance, it's becoming increasingly important for kids to develop skills that will prepare them for the future. One such skill is coding, and more specifically, coding artificial intelligence (AI). Teaching kids how to code AI not only helps them understand how technology works but also encourages critical thinking, problem-solving, and creativity. In this blog post, we will explore the answers to some common questions parents have about teaching kids AI and provide fun and educational ways to introduce them to this exciting field.

How do I get started teaching my child how to code AI?

Getting started with teaching your child how to code AI can be an exciting journey for both of you. Here are a few steps to help you get started:

What are the best coding languages to teach kids for AI?

When it comes to teaching kids coding languages for AI, there are a few options that are particularly well-suited for beginners:

1. Scratch: Scratch is a visual programming language designed specifically for kids. It uses colorful blocks that snap together, making it easy for young learners to understand and create their own interactive stories, games, and animations.

2. Python: Python is a versatile and widely used programming language. While it may have a steeper learning curve compared to Scratch, Python offers more advanced capabilities and is a popular choice for AI development. There are also kid-friendly Python resources available, such as "Python for Kids" books or online tutorials.

3. Blockly: Blockly is another visual programming language that simplifies coding by using interlocking blocks. It is often used as a stepping stone to more complex languages like JavaScript or Python. Blockly provides a gentle introduction to coding concepts and can be a great starting point for young learners.

Are there any coding camps or courses for kids specifically focused on AI?

Yes, there are coding camps and courses specifically focused on AI for kids. These programs provide a structured learning environment and often include hands-on projects, group activities, and expert guidance. Here are a few examples:

1. AI4K12 Summer Camp: AI4K12 offers summer camps that introduce kids to the world of AI. Through interactive sessions, coding challenges, and team projects, kids get hands-on experience with AI development.

2. CodeWizardsHQ: CodeWizardsHQ offers online coding courses for kids, including AI-focused programs. These courses are led by experienced instructors and provide a comprehensive curriculum designed to teach kids the fundamentals of coding AI.

3. MIT App Inventor: MIT App Inventor offers online courses that teach kids how to create mobile apps using AI. These courses are self-paced and provide step-by-step instructions, making them suitable for kids of different skill levels.

What are some fun and educational ways to introduce kids to AI coding?

Introducing kids to AI coding can be both fun and educational. Here are a few ideas to make the learning process enjoyable:

What are some tips for teaching kids how to think like AI developers?

Teaching kids how to think like AI developers can help them develop critical thinking and problem-solving skills. Here are some tips to encourage AI thinking:

What are some resources available to help parents teach their kids how to code AI?

Fortunately, there are numerous resources available to help parents teach their kids how to code AI. Here are a few worth exploring:

How can I make sure my child is learning about ethical AI development?

Teaching kids about ethical AI development is crucial to ensure they understand the impact of their creations. Here are some ways to incorporate ethical considerations into their AI education:

What are some of the benefits of teaching kids how to code?

Teaching kids how to code offers a wide range of benefits beyond just AI education. Here are some of the key advantages:

How can I help my child stay motivated & engaged in learning?

Keeping your child motivated and engaged in learning is essential for their continued progress. Here are some tips to help:

1. Set goals: Encourage your child to set achievable goals and celebrate their accomplishments along the way. Breaking down larger goals into smaller milestones can help them stay motivated.

2. Provide challenges: Offer coding challenges or projects that align with your child's interests. This will keep them engaged and excited about learning new concepts.

3. Offer rewards: Consider providing rewards or incentives for completing coding tasks or reaching specific milestones. Rewards can be as simple as extra screen time or a special treat.

4. Encourage collaboration: Encourage your child to collaborate with peers or join coding communities where they can share their projects, seek feedback, and learn from others.

5. Make it fun: Incorporate gamification elements into coding activities to make them more enjoyable. Use coding games, interactive tutorials, or even create coding-themed challenges for your child.

What are some of the challenges

of teaching kids how to code AI?

Teaching kids how to code AI can be challenging, but it is also a rewarding experience. Here are some of the challenges you may face:

The abstract nature of AI: AI concepts can be abstract and difficult for kids to grasp.

The lack of resources: There are not as many resources available for teaching kids how to code AI as there are for traditional programming languages.

The rapid pace of change: AI is constantly evolving, so it can be challenging to keep up with the latest technologies and trends.

The need for a strong foundation in math and science: AI coding requires a strong foundation in math and science, which some kids may not have.

The potential for bias: AI algorithms can be biased, so it is important to teach kids about the ethical implications of AI development.

Conclusion

Teaching kids AI education is an exciting and rewarding journey that can prepare them for the future. By starting with the basics, exploring AI concepts, and using fun and educational resources, you can help your child develop coding skills and think like AI developers. Remember to emphasize ethical considerations, highlight the benefits of coding, and keep your child motivated and engaged throughout their learning journey. With the right guidance and resources, your child can embark on a path to becoming a skilled AI coder and embrace the opportunities that lie ahead.

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A Beginner's Guide to Teaching Kids AI Education: Fun and Effective Ways to Get Started | AI Education for Kids

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Unlock the world of AI for kids with our beginner's guide. Explore easy-to-learn coding languages, interactive AI tools, and creative projects to inspire young minds. Ideal for parents and educators, this guide makes AI learning accessible, fun, and ethically sound, preparing children for a tech-forward future.

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Evaluation Exploration Toolkit

This is a toolkit for you to rummage around in, taking questions to ask and ways to think from each. No one set of questions has all the answers - it's up to you, the intrepid information explorer, to assemble your expeditionary tools, as you evaluate the information you find.

Information is created for a reason. Nothing slipped & fell and ended up on the internet, or in print, or on TV. It takes an act of human intentionality to create and publish information. This toolkit will give you a starting point to pull back the curtain on what you read, watch, listen to, or experience.

SIFT: a set of 4 Moves for Web Evaluation

The "things to do" moves from information literacy expert Mike Caulfield.

SIFT is a helpful acronym for initially evaluating source credibility. SIFT ( from Mike Caulfield) stands for:

STOP. Pause and ask yourself if you recognize the information sourceand if you know anything about the website or the claim's reputation.
If not, use the four moves (below) to learn more. If you start getting too overwhelmed during the other moves, pause and remember your original purpose.

INVESTIGATE the source.
Take a minute to identify where this information comes from and to consider the creator's expertise and agenda. Is this source worth your time? Look at what others have said about the source to help with you these questions. (See the "Four Moves" below for more on investigating sources.)
(For example, a company that sells health food products is not the best source for information about health benefits/risks of consuming coconut oil. A research study funded by a pharmaceutical company is also suspect.)

FIND trusted coverage.
Sometimes it's less important to know about the source and more important to assess their claim. Look for credible sources; compare information across sources and determine whether there appears to be a consensus.
Again, use the Four Moves below.

TRACE claims, quotes, and media back to the original context.
Sometimes online information has been removed from its original context (for example, a news story is reported on in another online publication or an image is shared on Twitter). If needed trace the information back to the original source in order to recontextualize it.

Modified from Mike Caulfield's SIFT (Four Moves), which is licensed under a Creative Commons Attribution 4.0 International License.
Later, when you determine that the site is worth your time, you can analyze the source's content more carefully.
Information adapted from Rowan University's Campbell Library resources on Evaluating Online Sources.
Six Questions

What type of content is this?

Recognize first what kind of content you're looking at.
Is it a news story? Or is it an opinion piece? Is it an ad or what some people call native advertising produced by a company? Is it a reaction to someone else's content?

Who and what are the sources cited and why should I believe them?

News content usually cites sources for the information provided. These are the people quoted, or the documents or reports or data being referred to.

Evidence: What's the evidence and how was it vetted?

Evidence is the proof that the sources offer for what they know. It overlaps with how close someone is to an event. But even highly credentialed sources may begin to speculate sometimes. They may be guessing.
So, first, identify the evidence that any source is offering. Circle it. Write it down. Do it as an exercise a couple times. It becomes easy to recognize.

Interpretation: Is the main point of the piece proven by the evidence?

Most media content offers a thesis, or main point, of some kind [...] ask whether this main point makes sense, and whether the conclusions are supported by the evidence offered.

Completeness: What's missing?

Most content should lead to more questions. An important step in being a critical, questioning consumer is to ask yourself what you don't understand about a subject. Look back at the piece. Did you miss something? Or was it not there?

Knowledge: Am I learning every day what I need?

Think about what media you consumed yesterday. What did you learn about? What did you read about?

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Research Guides: Research Strategies: Evaluation Toolkit

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Research Guides: Research Strategies: Evaluation Toolkit

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Humans Are Biased. Generative AI Is Even Worse

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Text-to-image models amplify stereotypes about race and gender — here’s why that matters

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What Is AI? | Artificial Intelligence | What is Artificial Intelligence? | AI In 5 Mins |Simplilearn