Tools & Platforms
New Faculty Member Shiyan Jiang on Bringing AI to Every Classroom
Newswise — As one of Penn GSE’s newest faculty members, Shiyan Jiang is helping expand what AI education can look like—and who it’s for. She doesn’t believe AI should be confined to computer science classes or taught only by tech experts. Instead, she’s designing curriculum and professional learning that help educators across all subjects bring AI into their classrooms in ways that are accessible, meaningful, and rooted in identity. In this Q&A, Jiang shares her vision for inclusive AI education, what drew her to Penn GSE, and why she believes every teacher can be an AI educator.
Q: What first sparked your interest in education and technology?
A: What sparked my interest wasn’t just the excitement of building software or exploring new technologies—it was the realization that technology can transform how we experience learning.
As an undergraduate, I was deeply engaged in developing augmented reality tools that made textbooks come alive—books that didn’t just sit on a desk, but responded to the reader, invited interaction, and sparked curiosity. That experience taught me something powerful: when students can see, touch, and engage with ideas in dynamic ways, learning becomes more meaningful. It showed me that technology, when thoughtfully designed, can be a bridge between what students know and what they could imagine.
Q: Can you share a project or area of research you’re especially excited about right now?
A: I’m especially excited about our work on integrating AI across the curriculum in ways that are accessible, meaningful, and sustainable. We started with a simple but powerful idea: AI should be for all students—not just those in computer science classes. So, we created an AI curriculum for high school English Language Arts. But we soon realized that no single subject can capture the full range of what it means to understand AI. That led us to design short, discipline-specific modules—AI for ELA, AI for math, and AI for history—where each teacher contributes just 3–5 hours from their own subject lens, while students gain exposure to AI from multiple perspectives.
What excites me most now is shifting the narrative: AI doesn’t need to be a separate, specialized topic. It can show up in everyday teaching—through a 5-minute classroom discussion or a full 15-hour unit.
Every teacher has the potential to be an AI educator. So now, my work is focused on supporting teachers in building their AI educator identity, while also studying how students develop their AI learner identities. Because if we want AI education to be truly inclusive, we need to empower every teacher—not just a few—to bring AI into their classrooms.
Q: What drew you to Penn GSE?
A: What drew me to Penn GSE is its bold vision for what education can be. The school’s commitment to interdisciplinary research and leadership in educational innovation aligns perfectly with how I approach my own work—blending AI, data science, and learning sciences to reimagine what’s possible in classrooms.
I’ve long admired the translational work happening at Penn GSE. It’s a place where big ideas are not only welcomed but also supported and scaled. I see tremendous potential to partner with faculty, students, and practitioners at Penn GSE to keep pushing the boundaries of how we think about AI and the future of learning.
Q: How do you hope your work will make a difference for educators or students?
A: I want every student—not just those in computer science classes—to have the opportunity to understand, question, and shape the role of AI in their lives. My work is about making AI education more inclusive and relevant, so that students from all backgrounds can see themselves in AI careers and feel empowered to use data and technology to tackle the issues they care about.
For educators, I hope to remove the barriers that make AI feel intimidating or “not for them.” I design tools, curricula, and professional learning experiences that support teachers in confidently bringing AI into their classrooms—regardless of their subject area or technical background. Because ultimately, if we want AI education to reach all students, we need to equip all teachers to be part of that journey.
Q: What’s something about your research that you wish more people understood?
A: I wish more people understood that education—whether we’re teaching AI, data science, or any other subject—is not just about delivering knowledge. At its core, my research is about creating spaces where students can reflect on who they want to become. When we design learning experiences or build educational tools, the goal isn’t just to teach technical skills—it’s to help students see themselves as capable, curious, and powerful contributors to their communities and the world. Whether they end up working in AI or not, I want students to leave the classroom with a stronger sense of identity, agency, and purpose.
Q: Outside of work, what’s something you’re passionate about or enjoy doing?
A: Outside of work, I love creating creative data visualizations. For me, it’s not just about charts and graphs, but about finding beauty in patterns and helping people see information in new ways.
I’m also a passionate traveler—especially a food traveler. Wherever I go, the first place I want to visit is the local market. I love experiencing a culture through its food: the ingredients, the smells, the way people gather and cook. It’s a joyful and delicious way to connect with people and places.
Q: When you think about the growing role of AI in education, are you more hopeful or concerned—and why?
A: Honestly, my feelings have evolved over time—just like many others navigating this space. There have been moments when I’ve felt incredibly hopeful, seeing all the new possibilities AI opens up for teaching and learning. And there have been moments of concern, especially when I see issues of bias and over-reliance surface.
But I’ve come to realize that this kind of fluctuation is part of the exploration process—it’s normal when we’re working with something so new and transformative. Overall, I consider myself an AI optimist. I believe in engaging with these technologies thoughtfully, trying things out, and learning through doing. For me, it’s not about waiting for perfect solutions—it’s about building better ones through reflection, iteration, and inclusive design.
Tools & Platforms
Can the Middle East fight unauthorized AI-generated content with trustworthy tech? – Fast Company Middle East
Since its emergence a few years back, generative AI has been the center of controversy, from environmental concerns to deepfakes to the non-consensual use of data to train models. One of the most troubling issues has been deepfakes and voice cloning, which have affected everyone from celebrities to government officials.
In May, a deepfake video of Qatari Emir Sheikh Tamim bin Hamad Al Thani went viral. It appeared to show him criticizing US President Donald Trump after his Middle East tour and claiming he regretted inviting him. Keyframes from the clip were later traced back to a CBS 60 Minutes interview featuring the Emir in the same setting.
Most recently, YouTube drew backlash for another form of non-consensual AI use after revealing it had deployed AI-powered tools to “unblur, denoise, and improve clarity” on some uploaded content. The decision was made without the knowledge or consent of creators, and viewers were also unaware that the platform had intervened in the material.
In February, Microsoft disclosed that two US and four foreign developers had illegally accessed its generative AI services, reconfigured them to produce harmful content such as celebrity deepfakes, and resold the tools. According to a company blog post tied to its updated civil complaint, users created non-consensual intimate images and explicit material using modified versions of Azure OpenAI services. Microsoft also stated it deliberately excluded synthetic imagery and prompts from its filings to avoid further circulation of harmful content.
THE RISE OF FAKE CONTENT
Matin Jouzdani, Partner, Data Analytics & AI at KPMG Lower Gulf, says more and more content is being produced through AI, whether it’s commentary, images, or clips. “While fake or unauthorized content is nothing new, I’d say it’s gone to a new level. When browsing content, we increasingly ask, ‘Is that AI-generated?’ A concept that just a few years ago barely existed.”
Moussa Beidas, Partner and ideation lead at PwC Middle East, says the ease with which deepfakes can be created has become a major concern.
“A few years ago, a convincing deepfake required specialist skills and powerful hardware. Today, anyone with a phone can download an app and produce synthetic voices or images in minutes,” Beidas says. “That accessibility means the issue is far more visible, and it is touching not just public figures but ordinary people and businesses as well.”
Though regulatory frameworks are evolving, they still struggle to catch up to the speed of technical advances in the field. “The Middle East region faces the challenge of balancing technological innovation with ethical standards, mirroring a global issue where we see fraud attempts leveraging deepfakes increasing by a whopping 2137% across three years,” says Eliza Lozan, Partner, Privacy Governance & Compliance Leader at Deloitte Middle East.
Fabricated videos often lure users into clicking on malicious links that scam them out of money or install malware for broader system control, adds Lozan.
These challenges demand two key responses: organizations must adopt trustworthy AI frameworks, and individuals must be trained to detect deepfakes—an area where public awareness remains limited.
“To protect the wider public interest, Digital Ethics and the Fair Use of AI have been introduced and are now gaining serious traction among decision-makers in corporate and regulatory spaces,” Lozan says.
DEFINING CONSENT
Drawing on established regulatory frameworks, Lozan explains that “consent” is generally defined as obtaining explicit permission from individuals before collecting their data. It also clearly outlines the purpose of the collection—such as recording user commands to train cloud-based virtual assistants.
“The concept of proper ‘consent’ management can only be achieved on the back of a strong privacy culture within an organization and is contingent on privacy being baked into the system management lifecycle, as well as upskilling talent on the ethical use of AI,” she adds.
Before seeking consent, Lozan notes, individuals must be fully informed about why their data is being collected, who it will be shared with, how long it will be stored, any potential biases in the AI model, and the risks associated with its use.
Matt Cooke, cybersecurity strategist for EMEA at Proofpoint, echoes this: “We are all individuals, and own our appearance, personality, and voice. If someone will use those attributes to train AI to reproduce our likeness, we should always be asked for consent.”
There’s a gap between technology and regulation, and the pace of technological advancement has seemingly outstripped lawmakers’ ability to keep up.
While many ethically minded companies have implemented opt-in measures, Cooke says that “cybercriminals don’t operate with those levels of ethics and so we have to assume that our likeness will be used by criminals, perhaps with the intention of exploiting the trust of those within our relationship network.”
Beidas simplifies the concept further, noting that consent boils down to three essentials: people need to know what is happening, have a genuine choice, and be able to change their mind.
“If someone’s face, voice, or data is being used, the process should be clear and straightforward. That means plain language rather than technical jargon, and an easy way for individuals to opt out if they no longer feel comfortable,” he says.
TECHNOLOGY SAFEGUARDS
Still, the idea of establishing clear consent guidelines often seems far-fetched. While some leeway is given due to the technology’s relative newness, it is difficult to imagine systems capable of effectively moderating the sheer volume of content produced daily through generative AI, and this reality is echoed by industry leaders.
In May, speaking at an event promoting his new book, former UK deputy prime minister and ex-Meta executive Nick Clegg said that a push for artist consent would “basically kill” the AI industry overnight. He acknowledged that while the creative community should have the right to opt out of having their work used to train AI models, it is not feasible to obtain consent beforehand.
Michael Mosaad, Partner, Enterprise Security at Deloitte Middle East, highlights some practices being adopted for generative AI models.
“Although not a mandatory requirement, some Gen AI models now add watermarks to their generated text as best practice,” he explains.
“This means that, to prevent misuse, organizations are embedding recognizable signals into AI-generated content to make it traceable and protected without compromising its quality.”
Mosaad adds that organizations also voluntarily leverage AI to fight AI, using tools to prevent the misuse of generated content by limiting copying and inserting metadata into text.
Expanding on the range of tools being developed, Beidas says, “Some systems now attach content credentials, which act like a digital receipt showing when and where something was created. Others use invisible watermarks hidden in pixels or audio waves, detectable even after edits.”
“Platforms are also introducing their own labels for AI-generated material. None of these are perfect on their own, but layered together, they help people better judge what they see.”
GOVERNMENT AND PLATFORM REGULATIONS
Like technology safeguards, government and platform regulation are still in the air. However, their responsibility remains heavy, as individuals look to them to address online consent violations.
While platform policies are evolving, the challenge is speed. “Synthetic content can spread across different apps in seconds, while review processes often take much longer,” says Beidas. “The real opportunity lies in collaboration—governments, platforms, and the private sector working together on common standards such as watermarking and provenance, as well as faster response mechanisms. That is how we begin to close the gap between creation and enforcement.”
However, change is underway in countries such as Qatar, Saudi Arabia, and the UAE, which are adopting AI regulations or guidelines, following the example of the European Union’s AI Act.
Since they are still in their early stages, Lozan says, “a gap persists in practically supporting organizations to understand and implement effective frameworks for identifying and managing risks when developing and deploying technologies like AI.”
According to Jouzdani, since the GCC already has a strong legal foundation protecting citizens from slander and discrimination, the same principles could be applied in AI-related cases.
“Regulators and lawmakers could take this a step further by ensuring that consent remains relevant not only to the initial use of content but also to subsequent uses, particularly on platforms beyond immediate jurisdiction,” he says, adding the need to strengthen online enforcement, especially when users remain anonymous or hidden.
Tools & Platforms
Exploring AI Agents’ Implementation in Enterprise and Financial Scenarios

Recently, the “Opinions on Deeply Implementing the ‘Artificial Intelligence +’ Initiative” issued by the State Council clearly stated that by 2027, the penetration rate of new – generation intelligent terminals and AI agents should exceed 70%, marking that the “AI agent economy” has entered an accelerated implementation phase. Against this policy background, the 3rd China AI Agent Annual Conference will be held in Shanghai on November 21st. The conference, themed “Initiating a New Intelligent Journey”, is hosted by MetaverseFamily. It focuses on two core tracks: enterprise – level and financial AI agents, bringing together the forces from upstream and downstream of the industrial chain to solve the pain points in the implementation of agent technologies and promote the effective implementation of the “Artificial Intelligence +” policy.
Two Core Segments Drive to Create a “Benchmark Platform” for Industry Exchange
As an important industry event after the implementation of the “Artificial Intelligence +” policy, this conference takes “practicality” and “precision” as its core. Through the form of “setting the tone at the main forum + solving problems at sub – forums + empowering through special sessions”, it provides participants with all – dimensional communication opportunities.
The Main Forum Focuses on AI Agent Trends and Determines the Technological Direction: In the morning, industry experts will discuss “the latest development and future opportunities of AI agents”, deeply analyze three technological paths: multimodal fusion, tool enhancement, and memory upgrade. At the same time, in line with the requirements of the “Opinions”, they will explore how agents can be deeply integrated with six key sectors, providing direction for enterprise layout.
Sub – forums Target “Enterprise – level and Financial AI Agents” and Provide Practical Solutions: Two sub – forums are set up in the afternoon to precisely meet the needs of different fields. Among them, the sub – forum on “Enterprise – level AI Agents Driving Marketing and Business Transformation” will break down the practical methods of local deployment of agents and database construction, share cases of cost reduction through business process automation, and help enterprises transform technologies into actual benefits. The sub – forum on “Financial AI Agents Reshaping the Industry’s Future” focuses on topics such as the technical principle of the 7×24 “risk – control sentinel” and the upgrade of intelligent customer service driven by large models, providing references for financial institutions to balance innovation and compliance.
Strengthen Resource Matching
The conference also features in – depth breakdowns of over 10 benchmark cases, a fireside chat among agent leaders, an annual award ceremony, and over 15 technology demonstration and experience areas. Participants can experience up close the application of agents in scenarios such as contract review and risk – control interception, and connect with over 300 industry professionals.
Supported by High – level Decision – Makers and Covering the Entire Industrial Chain
This conference has attracted the core forces of the AI agent industrial chain. The participants are characterized by a “high – end” profile. According to statistics, 30% of the participants are enterprise chairmen/general managers, and 25% are management personnel, covering key departments such as planning, marketing, information technology, and business, which can directly promote the implementation of cooperation.
As the conference organizer, MetaverseFamily is a hub – type media platform in the AI and metaverse fields. It has rich industry resources and event experience, providing strong support for the effectiveness of the conference. So far, the platform has held over 20 offline AI and metaverse conferences and over 40 online events, covering over 100,000 industry practitioners and having over 20,000 high – quality private WeChat group members. At the same time, it has successfully facilitated over 20 business cooperations, including the investment promotion project in Nanjing Niushoushan, the metaverse business cooperation with Mobile Tmall, and the upgrade of the AI shopping experience in an outlet mall, which can effectively connect resources and promote cooperation for participants.
In addition to the core topics, the “2025 AI Agent Annual Award Ceremony” at the conference is also worth looking forward to. The winners of heavy – weight awards such as the “Top 10 AI Agent Influential Brands of 2025” and the “Model Award for Financial AI Agents” are about to be announced.
Contact Us
Zhi Shu: 159 0191 1431 Alex.gan@ccglobal.com.cn
(Event Registration)
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