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Critical Thinking About Generative AI
Generative AI is reshaping how we create, communicate, and engage with the world鈥攂ut what do we gain, and what do we risk losing? This thought-provoking guide challenges you to move beyond fear or hype, applying critical thinking to AI鈥檚 evolving role in media, creativity, ethics, and society.
Communication and media scholars think critically about the introduction of new technologies, exploring what society gains and loses as new tools for communicating and new forms of media production and distribution become integrated into society. Rather than be motivated by fear of a new technology or a tendency to ask if a new technology is 鈥済ood鈥 or 鈥渂ad,鈥 communication and media scholars apply critical thinking strategies to consider its benefits and challenges as well as its design and uses. Through these lenses, scholars argue that the design of each technology, including Artificial Intelligence (AI), affords us the ability to use it in certain ways, including uses that we find beneficial and those that we find harmful. At the same time, we understand that a technology does not determine its own impact on the world; instead, we can think about how those who design, distribute, profit from, and use the technology are all part of the m茅lange of factors that impact how a new technology will be integrated into and possibly change society. Since AI is always developing, here are some questions you can ask to think critically about its value, use, and impact:
We encourage you to spend some time thinking about your own answers to these questions.
What might we gain and/or lose from the introduction of Generative AI (GenAI)?
As many of us have experienced, GenAI can increase efficiency and process large amounts of information. It may even increase creativity by helping us to think outside of the confines of human thought. On the one hand, these tools could lead us to develop complex perspectives and stronger evidence-based arguments. On the other hand, AI processes could also lead us to rely less on our own memories and analytical skills, potentially atrophying our abilities to think critically, develop expertise, and exercise moral judgments.
What moral codes and ethical principles does AI use as it creates communications and media?
Like all new technologies, AIs鈥 processes are encoded with the biases of its developers. In a capitalist society, developers are likely to value profit over human wellness. In addition, some scholars are concerned that because GenAI relies on user prompts and develops its intelligence by building on existing information and patterns, it is not equipped to challenge social norms or stereotypes. It is essential to consider when it is imperative for AI to value humanity or ecology over profit. If we first specify, through prompts, what a GenAI tool should value, it may abide, but what about when we don鈥檛? In other words, what is or should be the AI moral default? Alternatively, can AI be developed that helps users critically reflect on their own biases and consider alternative ideologies?
How might AI impact the creative industries?
Much of the buzz surrounding GenAI has focused on its potential uses in artistic endeavors, such as creating literature, music, and video games. It鈥檚 worth considering the potential benefits and challenges of using AI in these areas. AI might lower the barrier to entry for creative work and thus help even more people create and share their artistic visions with the world. Yet it鈥檚 possible that AI trained primarily on media content that reflects predominant power dynamics and stereotypes would largely generate output reflecting those same power dynamics and stereotypes, thus impeding the creation and spread of innovative and resistive creative ideas and expressions. AI has already provoked a 鈥渃risis鈥 in intellectual property, with artists expressing concern that AI is using their works without permission and threatening their livelihood. AI thus raises critical questions about what it means to 鈥渙wn鈥 an idea or creative expression as well as the meaning of creativity in general.
As users who interact with new and expanding AI tools, how can we help shape their use?
It鈥檚 important to recognize that AI is a technology made by and ultimately used by humans, thus giving us influence over how AI is designed and implemented. New literacies must be developed to help people learn how to use AI safely and responsibly. New norms, expectations, and regulations are needed to make sure AI is used ethically and to hold those accountable who fail to do so. Serious consideration must also go into developing and implementing strategies to prevent AI from exacerbating the digital divide. Who will have access to the highest quality AI? Will it remain free and open or will those with greater privilege, have access to more powerful and advanced tools? What might be the long term socio-political and economic impact of this divide?
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As artificial intelligence seeps into every facet of life, 蜜桃工作室 scholars are working to harness the technology鈥檚 potential to transform teaching and research. While the road ahead is fraught with uncertainty, these 蜜桃工作室 experts see a fairer and safer AI-driven future.
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Living the AI Experiment
As artificial intelligence seeps into every facet of life, 蜜桃工作室 scholars are working to harness the technology鈥檚 potential to transform teaching and research. While the road ahead is fraught with uncertainty, these 蜜桃工作室 experts see a fairer and safer AI-driven future.
When computer science and philosophy professor James Brusseau, PhD, introduced his students to the Caffeinated Professor, a generative artificial intelligence (AI) chatbot trained on his , he wasn鈥檛 trying to replace traditional teaching by handing the classroom over to a robot.
He was embarking on an experiment into uncharted educational territory, a journey without a map and only one direction of travel.
鈥淚 don鈥檛 know all the ways that it will help and hurt my students,鈥 said Brusseau, who unveiled the AI professor to his Philosophy 121 class this semester. Students are encouraged to converse with the bot day or night, engaging in conversation just as they might with him. 鈥淲hen answers are a few keystrokes away, there鈥檚 a clear pedagogical negative to introducing a tool like this.鈥
鈥淏ut if I didn鈥檛 build this, someone else would have,鈥 he added. 鈥淲hile I can鈥檛 control the world鈥檚 鈥楢I experiment,鈥 I do have the opportunity to see for myself how it鈥檚 working.鈥
The rise of generative AI鈥攖ools like ChatGPT, Gemini, and Grok that generate original text, images, and videos鈥攈as sent shockwaves through many industries. For some observers, fear is the dominant emotion, with concerns that AI could take jobs or lead to humanity鈥檚 downfall.
Professors and researchers at 蜜桃工作室, however, see a different future. For them, AI anxiety is giving way to a cautious acceptance of a technology that鈥檚 transforming how we live, work, study, and play. While creators urge caution and experts debate regulations, scholars are concluding that, for better or worse, AI is here to stay.
The real question is what we choose to do with that actuality.
At 蜜桃工作室, experimentation is the only way forward. In Fall 2024, 蜜桃工作室 included an AI course鈥斺攖o its core curriculum for undergraduates, bringing the number of courses that incorporate AI at the undergraduate and graduate levels to 39.
鈥淲hile I can鈥檛 control the world鈥檚 鈥楢I experiment,鈥 I do have the opportunity to see for myself how it鈥檚 working.鈥
蜜桃工作室 is also leading the way in cross-disciplinary AI and machine learning research. At the 蜜桃工作室 AI Lab housed in the Seidenberg School of Computer Science and Information Systems, led by pioneering AI researcher Christelle Scharff, PhD, faculty, staff, and students integrate their knowledge areas into collective problem solving powered by the technology.
In doing so, 蜜桃工作室鈥檚 academics are writing and revising the script for how to balance the dangers and opportunities that AI presents. 鈥淲e鈥檙e living in a heuristic reality, where we experiment, see what happens, and then do another experiment,鈥 said Brusseau.
A Defining Moment
Jessica Magaldi鈥檚 AI experiment began with revenge porn. Early in her career, the award-winning Ivan Fox Scholar and professor of business law at the Lubin School of Business studied intellectual property law and transactions for emerging and established companies.
In 2020, she turned her attention to laws criminalizing the illegal sharing of sexually explicit images or videos of a person online without consent. Shockingly, most were toothless, she said, and there was very little public or political appetite to sharpen them.
Now, fast forward to January 2024, when fake sexually . Public outrage was immediate. Users demanded accountability, and fans initiated a 鈥淧rotect Taylor Swift鈥 campaign online. .
For Magaldi, something didn鈥檛 add up. 鈥淲e were at a moment when AI generated content that everyone knows is fake was producing more outrage than so-called revenge porn photos, images that are real.鈥 Understanding that contradiction could offer clues on how to draft laws and legislation that are more effective for the victims, she said.
Eventually, it might even teach us something about ourselves. 鈥淢y greatest hope is that we can use what we learn about the differences between how we feel about what is real and what is AI to explore what that means for us and our collective humanity,鈥 she said.
Optimism Grows
Harnessing the benefits of AI is also what occupies Brian McKernan, PhD, an assistant professor of communication and media studies at the Dyson College of Arts and Sciences.
McKernan, who describes himself as cautiously optimistic about AI, would be excused for taking a less rosy view of the technology. His research areas include misinformation, cognitive biases, and political campaign transparency鈥攖opics where the use of AI is rarely benevolent. In a of the 2020 US presidential election, McKernan and his collaborators found that President Donald Trump used the massive exposure popular social media platforms offer in an attempt to sow distrust in the electoral process.
鈥淭here are great uses for AI, particularly in cases with huge amounts of data. But we will always need humans involved in verifying."
And yet, McKernan remains upbeat, an optimism stemming from the fact that AI helps him keep tabs on what politicians are saying, and doing, online.
鈥淚t鈥檚 a data deluge,鈥 he said. To help sort through it, McKernan and colleagues at the Illuminating project, based at Syracuse University train supervised AI models to classify and analyze social media content. Researchers check the performance of the models before making their findings public.
鈥淭here are great uses for AI, particularly in cases with huge amounts of data. But we will always need humans involved in verifying,鈥 he said.
Racing to Regulate?
To be sure, there are social and ethical dangers inherent in AI鈥檚 application鈥攅ven when people are at the keyboard. One concern is access. Many generative AI tools are free, but they won鈥檛 be forever. When people can鈥檛 afford 鈥渢he shiniest tools,鈥 McKernan said, the digital divide will deepen.
Other challenges include maintaining data privacy, expanding availability of non-English tools, protecting the intellectual property of creators, and reducing biases in code. Even is an area of increasing concern for security experts.
Emilie Zaslow, PhD, a professor and chair of communication and media studies at 蜜桃工作室, said given these concerns, eventually, a regulatory framework for AI might be wise.
鈥淚n media, we have examples of both government regulatory oversight, through the Federal Communications Commission, for example, and industry self-regulation, such as the Motion Picture Association film rating system,鈥 Zaslow said. 鈥淭here is also government involvement in evaluating new consumer products; take the Food and Drug Administration, for example. Every time a new drug comes to market, the FDA evaluates it, tests it, and decides whether it gets released and with what kind of warnings.鈥
鈥淭here should be increased regulatory oversight for technology,鈥 she said.
Regulations are emerging. In Europe, bans certain applications deemed to pose an 鈥渦nacceptable risk鈥 to citizens. Punishable programming includes social scoring systems, real-time facial recognition and other forms of biometric identification that categorize people by race, sex life, sexual orientation and other attributes, and 鈥渕anipulative鈥 AI tools.
up to $35.8 million or 7% of their global annual revenues鈥攚hichever amount is higher.
Brusseau, while sensitive to the dangers, doubts that the punitive approach will pay off. 鈥淭he internet has no geography; it isn鈥檛 anywhere,鈥 he said. 鈥淗ow do we prohibit something that isn't anywhere?鈥
鈥淭here should be increased regulatory oversight for technology.鈥
He suggests a different approach: using technology to regulate itself. He calls this , the idea that the most effective way to approach risks raised by innovation is with still more innovating.
In a , Brusseau examined how TELUS, a Canadian telecommunications company, developed an automated safety tool to monitor its customer-serving chatbot. When the safety tool detected hallucinations, phishing threats, or privacy risks in the chatbot鈥檚 answers, it flagged them for human review.
鈥淲hile the purity of theoretical positions is blurred by real-world ambiguities,鈥 Brusseau wrote, 鈥渢he TELUS case illustrates how the acceleration strategy transforms AI ethics into an innovation catalyst.鈥
Risks Worth Taking
Ask ChatGPT whether it鈥檚 dangerous, and its response is unequivocal: 鈥淚鈥檓 here to help and have meaningful conversations.鈥
Ask ChatGPT whether AI is dangerous, the reply is a bit murkier: 鈥淚t depends on how it's used.鈥
But point out that ChatGPT is AI, and the contradiction isn鈥檛 lost on the technology itself. 鈥淲hat I meant to convey is that I am designed to be helpful, safe, and non-threatening. But it鈥檚 true that, like any tool, the potential for harm exists if used irresponsibly.鈥
When scholars and historians look back at this era of AI experimentation, they may be similarly conflicted. Magaldi, who understands how devastating sexually explicit deepfake images can be, also recognizes the usefulness of AI鈥檚 creativity. In Spring 2024, she even used AI to help her flesh out an idea for a class on Taylor Swift. She did it, in part, as an exercise for herself to use AI in a creative way.
鈥淚'm not worried in the least. Humans produce knowledge through causality, while machines do it exclusively through correspondence. They reason wrong.鈥
鈥淲ith ChatGPT, I was able to build an entire music industry law class based on ,鈥 Magaldi said. After lots of tweaking, she ended up with the syllabus for a three-credit class exploring the singer鈥檚 experiences with copyright infringement, music industry contracts, trademark law, and ticketing practices.
It was a massive success. were made about the class, registration for the class closed in minutes, and students are eager for it to run again.
This type of human-AI interaction鈥攗sing the technology as a 鈥渢hought partner,鈥 as Magaldi puts it鈥攊s the sweet spot in AI鈥檚 societal integration.
It鈥檚 also why Brusseau is upbeat. 鈥淚'm not worried in the least,鈥 he said. 鈥淗umans produce knowledge through causality, while machines do it exclusively through correspondence. They reason wrong.鈥
That certainty, however, doesn鈥檛 mean he has all the answers. With AI, there are only questions. 鈥淟ike buying a one-way plane ticket, it鈥檚 not the destination that matters, but the journey,鈥 he said. 鈥淭hat鈥檚 why I built the Caffeinated Professor鈥攖o see where it takes us.鈥
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Haub Law鈥檚 Mock Trial Team Finishes Strong in the Queens County District Attorney's Office 10th Annual Mock Trial Competition
The Elisabeth Haub School of Law at 蜜桃工作室鈥檚 Mock Trial Team recently competed in the , which took place in the court facilities of the Queens Criminal Court. The 蜜桃工作室 Haub Law team consisting of Skyler Pozo (2L), Maiya Aubry (2L), Alexa Saccomanno (2L), and James Page (2L), finished in second place out of the eighteen nationally ranked law schools who competed.
The Elisabeth Haub School of Law at 蜜桃工作室鈥檚 Mock Trial Team recently competed in the , which took place in the court facilities of the Queens Criminal Court. The 蜜桃工作室 Haub Law team consisting of Skyler Pozo (2L), Maiya Aubry (2L), Alexa Saccomanno (2L), and James Page (2L), finished in second place out of the eighteen nationally ranked law schools who competed. During the intense competition, students competed before senior prosecutors and members of the defense bar with judges from Queens and Brooklyn presiding over the competition, along with prosecutors and defense attorneys.
The Haub Law Mock Trial Team successfully made it through two preliminary rounds, a blind quarterfinal round, semi-finals, before finishing in second place during the final round. 鈥淚t was a challenging competition with some of the best and brightest law students throughout the country, but I鈥檓 proud to say that our student advocates rose to the occasion,鈥 said Luis Felix 鈥15, who coached the 蜜桃工作室 Haub Law team. 鈥淭heir dedication, hard work and knowledge of the fact pattern was reflected in their strong finish, and I look forward to seeing what else they accomplish in the courtroom.鈥 Alexa Saccomanno (2L) was also awarded the individual award of Best Opening Statement.
鈥淭he performance by our 2L students demonstrates both the strength and depth of our program,鈥 said Professor Louis Fasulo, Director of Advocacy Programs and Professor of Trial Practice. 鈥淭hese students along with the support of Coach Felix makes us all proud and is a major highlight of this year鈥檚 competitions.鈥