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AI has taken the internet by storm since its rise in popularity nearly a year ago, from generating images to writing essays in seconds. Today, AI seems to be embraced to a certain degree at Seton Hall, by being aware of some of its pros but also being aware of its cons.

The Department of Information Technology published a site called the Artificial Intelligence Resource Center, to guide faculty members in addressing the use of AI with strategies for integrating AI into curriculums, reducing AI-generated content by students and requesting consultations with the Teaching, Learning, and Technology Center Instructional Designer.

This new site will continue to change as more information is gathered, according to Paul Fisher, the director of the Teaching, Learning, and Technology Center and associate chief information officer.

We need to ensure the University community is aware of both the rewards this kind of technology can provide and the risks that it presents, Fisher said. For example, additions of AI in our security suite of software help us to weed out false positives and become aware of potential threats faster than before.

Fisher said that people can use AI with both positive and negative goals in mind.

Taking a shortcut with AI to write or analyze or some other skill wont make you very good at what you are trying to learn to do, he said. We need to make our students aware that in the long run, using AI will not get them to where they want to be.

He added the university licenses TurnItIn, a system that detects generative AI and other forms of plagiarism in written work and the department is actively looking at other tools to deploy that will help both faculty and students.

Some professors have expressed their worry over students relying on AI programs to do schoolwork.

Dr. Russell Sbriglia, associate professor and director of Undergraduate Literature Studies in the English Department, said that although some professors have proposed to do more in-class writing assignments to reduce the use of generative AI among students, students can still easily use ChatGPT in class as out of class.

My approach has thus far been to stress to students the limitations of ChatGPT, Sbriglia said. This includes modeling for students the kinds of errors to which generative AI software is prone. It also includes stressing just how integral writing is to the process of critical thinking.

He also said that students using AI software for their writing assignments outsource their ability to think critically.

It is through the very act of writing that we come to organize, construct, and even discover our thoughts on a given topic or text, he said. To skip that process altogether by using AI generative software is to curtail ones ability to think critically.

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He added that professors will need to become more nimble and creative when creating assignments that develop or test for the kinds of knowledge and skills that such programs simply cannot fake as generative AI continues to advance and become more sophisticated.

At the end of the day, artificial intelligence simply does not think like an actual human brain, Sbriglia said.

The English Department recently updated its Plagiarism Policy to address the use of generative AI, such as ChatGPT, amongst students stating that any use of AI tools for essays, journals, in-class writing assignments, etc. is in violation of the English Department Academic Integrity Policy, but with the exception of exercises developed by your professor.

Although some professors are worried about students relying on AI for their assignments, some professors have embraced the use of AI and adjusted their curriculum in a way their students can use it as a tool for learning instead of cheating.

Dr. Nada Khan, a professor in the Department of Chemistry and Biochemistry, said she is happy that AI is playing an important role in exploring new technologies and ideas.

Rather than worrying about students relying on AI, I work on tweaking my exams and assignments in a way that instead of cheating, copying, relying on AI, students can use it as a tool to expand their knowledge, Khan said.

She added that she uses different and new exam models and other ways to test her students knowledge, and it is easy for her to know if an exam was done with the help of AI.

Since I know the learning nature of my students during in-class work, it is easy for me to determine if the exam was completed with the help of AI, Khan said. This is another reason why I make them work on in-class assignments.

The Office of the Provost, the Center for Faculty Development, and the Teaching, Learning and Technology Center at Seton Hall will hold a panel discussion called Impact Talks Presents: Generative AI and Higher Education on Nov. 2 in Bethany Hall from 12:30 p.m.

The panel will host keynote speaker, Dr. Jason Gulya, professor at Berkeley College and chair of the Artificial Intelligence Council, along with Seton Hall faculty and student representatives sharing their thoughts on the rapid advancement of generative Artificial Intelligence (AI) and its impact on higher education.

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A year later, artificial intelligence remains a double-edged sword at ... - The Setonian

As the war between Israel and Hamas continues, people are turning to social media in search of reliable information about their family and relatives, events on the ground, and an understanding of where the current crisis might lead. The introduction of Generative Artificial Intelligence (GAI) toolssuch as deepfakes and synthetic audioare further complicating how the public engages with and trusts online information in an environment already rife with misinformation and inflammatory rhetoric. There is a dual problem of bad actors intentionally exploiting these tools to share misleading information, and their ability to cast doubt on any content with even the idea that it might be fake. This is leading to a dangerous erosion of trust in online content.

Fake news stories and doctored images are not unique to the current conflict in the Middle East; they have long been an integral part of warfare, with armies, states, and other parties using the media as an extension of their battles on the ground, in the air, and at sea. What has changed radically is the advent of digital technology. Any reasonably tech-savvy person with access to the internet can now generate increasingly convincing fake images and videos (deepfakes,) and audio, using GAI tools (such as DALL-E, that generates images from text,) and then distribute this fake material to huge global online audiences at little or no cost. Recent examples of such fakes include an AI-generated video supposedly showing First Lady Jill Biden condemning her own husbands support for Israel.

By using GAI to, for example, spread mis- and disinformation, bad actors are actively seeking not just to score propaganda victories, but also to pollute the information environment. Promoting a climate of general mistrust in online content means that bad actors need not even actively exploit GAI tools; the mere awareness of deepfakes and synthetic audio makes it easier for these bad actors to manipulate certain audiences into questioning the veracity of authentic content. This phenomenon has become known as the liars dividend.

In the immediate aftermath of Hamass brutal invasion of Israel on October 7, we have witnessed an increase in antisemitism and Islamophobia online as well as in the physical world. Images of Israelis brutally executed by Hamas have been widely distributed on social media. While these images have helped document the horrors of the war, they have also become fodder for misinformation. So far, we have not been able to confirm that generative AI images are being created and shared as part of large-scale disinformation campaigns. Rather, bad-faith actors are claiming that real photographic or video evidence is AI-generated.

On Wednesday, October 11, a spokesperson for Israeli Prime Minister Benjamin Netanyahu said that babies and toddlers had been found decapitated in the Kfar Aza kibbutz following the Hamas attack on October 7. In US President Joe Bidens address to the nation later that evening, he said that he had seen photographic evidence of these atrocities. The Israeli government and US State Department both later clarified that they could not confirm these stories, which unleashed condemnation on social media and accusations of government propaganda.

To counter these claims, the Israeli Prime Ministers office posted three graphic photos of dead infants to its X account on Thursday, October 12. Although these images were later verified by multiple third-party sources as authentic, they set off a series of claims to the contrary. The images were also shared by social media influencers, including Ben Shapiro of The Daily Wire, who has been outspoken in his support for Israel.

Critics of Israel, including self-described MAGA communist Jackson Hinkle, questioned the veracity of the images and claimed that they had been generated by AI. As supporting evidence, Hinkle and others showed screenshots from an online tool called AI or Not, which allows users to upload images and check if they were likely AI- or human-generated. The tool determined that the image Shapiro shared was generated by AI. An anonymous user on 4chan then went a step further and posted an image purporting to show the original image of a puppy about to undergo a medical procedure, alleging that the Israeli government had used this image to create the fake one of the infants corpse:

The 4chan screenshot was circulated on Telegram and X as well.

Other X users, including YouTuber James Klg, disputed Hinkles assertion, sharing their own examples where AI or Not determined that the image was human-generated. Hinkles post has received over 22 million impressions at the time of this writing, whereas Klgs has only received 156,000.

Our researchers at ADL Center for Tech & Society (CTS) replicated the experiment with AI or Not and got both results: When using the photo shared by the Israeli PMs X account, the tool determined it was AI. But when using a different version downloaded from Google image search, it determined the photo was human-generated. This discrepancy says more about the reliability of the tool than about any deliberate manipulation by the Israeli government. AI or Nots inconsistencies are well documented, especially its tendency to produce false positives.

The Jerusalem Post confirmed the images were indeed real and had been shown to US Secretary of State Anthony Blinken during his visit to the Israeli Prime Ministers office on October 12. In addition, Hany Farid, a professor at the UC Berkeley School of Information, says his team analyzed the photos and concluded AI wasn't used. Yet this is unlikely to convince social media users and bad-faith actors who believe the images were faked. Xs Community Notes feature, which crowdsources fact-checks from users, applied labels to some posts supporting the claim of AI generation and other labels refuting the claim:

This incident exposes a perfect storm of an online environment rife with misinformation and the impact that many experts feared generative AI could have on social media and the trustworthiness of information. The harm caused by the publics awareness that images can be generated by AI, and the so-called liars dividend that lends credibility to claims of real evidence being faked, outweigh any attempts to counter these claims. Optics AI or Not tool includes warning labels that the tool is a free research preview and may produce inaccurate results. But this warning is only as effective as the publics willingness to trust it.

CTS has already commented on the misinformation challenges that the Israel-Hamas war poses to social media platforms. Generative AI adds another layer of complexity to those challenges, even when it is not actually being used.

Amid an information crisis that is exacerbated by harmful GAI-created disinformation, social media platforms and generative AI developers alike have a crucial role to play in identifying, flagging, and if necessary, removing synthetic media disinformation. The Center for Tech & Society recommends the following for each:

Impose a clear ban on harmful manipulated content: In addition to regular content policies that ban misinformation in cases where it is likely to increase the risk of imminent harm or interference with the function of democratic processes, social media platforms must implement and enforce policies prohibiting synthetic media that is particularly deceptive or misleading, and likely to cause harm as a result. Platforms should also ensure that users are able to report violations of such a policy with ease.

Prioritize transparency: Platforms should maintain records/audit trails of both the instances that they detect of harmful media and the subsequent steps that they take upon discovery that such a piece of media is synthetically created. They should also be transparent with users and the public about their synthetic media policy and enforcement mechanisms. Similarly, as noted in the Biden-Harris White Houses recent executive order on artificial intelligence, AI developers must be transparent about their findings as they train AI models.

Proactively detect GAI-created content during times of unrest: Platforms should implement automated mechanisms to detect indicators of synthetic media at scale, and use them even more robustly than usual during periods of war and unrest. During times of crisis, social media platforms must increase resources to their trust and safety teams to ensure that they are well-equipped to respond to surges in disinformation and hate.

Implement GAI disclosure requirements for developers, platforms, and users: GAI disclosure requirements must exist in some capacity to prevent deception and harm. Requiring users to disclose their use of synthetic media and social media platforms to identify it can play a significant role in promoting information integrity. Disclosure could include a combination of labeling requirements, prominent metadata tracking, or watermarks to demonstrate clearly that a post involved the creation or use of synthetic media. As the Department of Commerce develops guidance for content authentication and watermarking to clearly label AI-generated content, industry players should prioritize compliance with these measures.

Collaborate with trusted civil society organizations: Now more than ever, social media platforms must be responsive to their trusted fact-checking partners and civil society allies flags of GAI content, and they must make consistent efforts to apply those labels, and moderate if necessary, before the content can exacerbate harm. Social media companies and AI developers alike should engage consistently with civil society partners, whose research and red-teaming efforts can help reveal systemic flaws and prevent significant harm before an AI model is released to the public.

Promote media literacy: Industry should encourage users to be vigilant when consuming online information and media. They may consider developing and sharing educational media resources with users, and creating incentives for users to read them. For instance, platforms can encourage users in doubt about a piece of content to consider the source of the information, conduct a reverse image-search, and check multiple sources to verify reporting.

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Generative Artificial Intelligence (GAI): Increasing the Fog of War ... - ADL

Birds

The intelligent birds, thought to be a nuisance by some, learn from consequences and can recognize resemblance between objects

Thu 26 Oct 2023 05.00 EDT

A new study has found that the way pigeons problem-solve matches artificial intelligence.

Often overlooked as a nuisance, pigeons are actually highly intelligent animals that can remember faces, see the world in vivid colors, navigate complex routes, deliver news and even save lives.

In the study, 24 pigeons were given a variety of visual tasks, some of which they learned to categorize in a matter of days, and others in a matter of weeks. The researchers found evidence that the mechanism that pigeons used to make correct choices is similar to the method that AI models use to make the right predictions.

Pigeon behavior suggests that nature has created an algorithm that is highly effective in learning very challenging tasks, said Edward Wasserman, study co-author and professor of experimental psychology at the University of Iowa. Not necessarily with the greatest speed, but with great consistency.

On a screen, pigeons were shown different stimuli, like lines of different width, placement and orientation, as well as sectioned and concentric rings. Each bird had to peck a button on the right or left to decide which category they belonged to. If they got it correct, they got food, in the form of a pellet; if they got it wrong, they got nothing.

Pigeons dont need a rule, said Brandon Turner, lead author of the study and professor of psychology at Ohio State University. Instead they learn through trial and error. For example, when they were given a visual, say category A, anything that looked close to that they also classified as category A, tapping into their ability to identify similarities.

Over the course of the experiments, pigeons improved their ability to make right choices from 55% to 95% of the time when it came to some of the simpler tasks. Presented with a more complex challenge, their accuracy went up from 55% to 68%.

Using more humble animals like pigeons, we can test how far they can go with a mind that is [we think] solely or mostly associative, said Onur Gntrkn, professor of behavioral neuroscience at Ruhr University Bochum who was not involved in the study. This paper shows how incredibly strong associative systems can be, how true cognition-like they are.

In an AI model, the main goal is to recognize patterns and make decisions. Pigeons, as research shows, can do the same. Learning from consequences, when not given a food pellet, pigeons have a remarkable ability to correct their errors. Similarity function is also at play for pigeons, by using their ability to find resemblance between two objects.

With just those two mechanisms alone, you can define a neural network or an artificial intelligent machine to basically solve these categorization problems, said Turner. It stands to reason that the mechanisms that are present in the AI are also present in the pigeon.

The researchers now aim to collaborate with scientists who study pigeons and their brains. They are hoping that these findings can have practical applications in better understanding human brain damage.

Maybe we can get some further insight into what is going on in that little bird brain, said Wasserman. Its a damn good brain it may be small in size, but they pack a punch when it comes to the capacity to learn.

No pigeons were harmed in the course of the study.

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Pigeons problem-solve similarly to artificial intelligence, research shows - The Guardian

Behind the jaw-dropping technologies that Nvidia, Apple, Broadcom, and many others put out is Taiwan Semiconductor Manufacturing (TSM 1.73%). TSMC -- as it's commonly called -- is the world's largest chip foundry and only makes chips on a contract basis, which allows it to stay neutral as competitors battle it out in the smartphone, GPU, and automotive worlds.

While its chips have always been cutting-edge, TSMC's latest technology had yet to hit the markets until recently. Its 3 nanometer (nm) chips are finally starting to contribute to revenue, making this an exciting time for TSMC investors. So, what's the big deal with these chips? Read on to find out.

Taiwan Semiconductor's 3 nm chips represent the next iteration in chip technology. By increasing the density, Taiwan Semiconductor can pack more transistors onto a single chip, making them more powerful or energy efficient (depending on how the designer configures the chip).

This allows for more powerful technologies to be launched by the likes of Nvidia or Apple. With the latest wave of artificial intelligence interest hitting various companies, the 3 nm chip launch couldn't have come at a better time.

While the legacy 5 nm chip still holds the lion's share of revenue, investors should expect 3 nm's revenue share to grow rapidly over the next few quarters.

Data source: Taiwan Semiconductor.

Conversely, the 7 nm revenue share has declined as 5 nm revenue has increased. Eventually, 3 nm will do the same to 5 nm chips, but that won't be for a few years. Regardless, now that 3 nm chips are starting to impact Taiwan Semiconductor's financial results materially, it's an exciting time for investors as they can finally see returns on the capital TSMC has invested into developing the process.

Despite the great news of the 3 nm chips' arrival, Taiwan Semiconductor still posted declining revenue in the third quarter. Because customers have excess inventory, demand for TSMC's chips has been lower in 2023. This contributed to revenue declining by 15% year over year in U.S. dollars. But management also sees signs of PC and smartphone demand returning, indicating that 2024 could be a great year for the company.

With a stronger outlook ahead, you'd think investors would get excited and pump the stock up, but that's not happening. Taiwan Semiconducutor's valuation is cheap from both a trailing- and a forward-earnings perspective.

TSM PE Ratio data by YCharts

With the stock trading at 15 times trailing and 18 times forward earnings, it's much cheaper than the S&P 500's 25 times trailing and 19 times forward earnings. This is despite the fact that Taiwan Semiconductor is one of the best-run businesses and is looking at huge future demand.

Taiwan Semiconductor is your investment if you're looking for a stock that can display growth characteristics while trading like a value stock. These two investing fields rarely intersect, but the results can be fantastic when they do.

The company is just starting to roll out its innovative 3 nm chip technology, which ultimately costs more than its predecessors. This incremental increase should drive its stock price higher, and investors ought to buy the stock now with at least a three- to five-year holding period in mind to capitalize on this transition.

Keithen Drury has positions in Taiwan Semiconductor Manufacturing. The Motley Fool has positions in and recommends Apple, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool recommends Broadcom. The Motley Fool has a disclosure policy.

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The Top Artificial Intelligence (AI) Chipmaker Is Finally Starting to ... - The Motley Fool