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“At Turnitin, we believe in human-centered AI. This means putting the human user at the center of research, development, and function. We seek to build AI that assists, strengthens, and scales human abilities—not replace them. Our work with AI furthers our mission to ensure that students, educators, and institutions have the power to make data-driven decisions,” states Senior Director of Machine Learning, Eric Wang.
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AI, as with all technology, ought to be designed with good intentions, and Turnitin is steadfast in its commitment to responsible AI. At Turnitin, AI is designed to help students, educators, and institutions advance integrity and learning outcomes, at scale.
Because AI relies heavily on its designers and engineers, we want to introduce you to our AI team at Turnitin. We aim to be inclusive and build a diverse team that makes continual improvements to ensure accessibility and fairness. As you read why they feel AI is important to learning and the reasons they dedicate their lives to AI design, we hope you see reflected in their answers Turnitin’s mission to uphold integrity and enable student learning. Because artificial intelligence is, bottom line, as good as its creators.
Eric Wang focuses on leveraging AI to improve learning experiences and promote academic integrity around the world. He says, “AI is one of the most powerful and transformative technologies in our society right now. It’s rare to work on something that has this sort of impact. I also appreciate how Turnitin AI takes a holistic approach to building AI into our products. AI can be a force of enormous good, so we think a lot about the impact of our technology on the learning journeys undertaken by our students, instructors, and institutions, and focus on building AI that amplifies the great things that are happening while also mitigating any harmful effects.”
“One of the most powerful things about AI,” says Eric, “is that it can distill patterns from data to make predictions. When used with care, these predictions can help guide us to make decisions with more thought, context, and consideration than without them. Education is about learning, but it's also a sequence of millions upon millions of decisions— what to prioritize and when, how to approach a problem, which student needs what kind of help, etc.—and by helping make each of those decisions a little bit better or more considered, we can have a huge impact on learning outcomes all around the world.”
Since his university studies in 2003, Andrew Nykonenko has worked with data on scientific and research projects. Andrew says, “The rise of AI has benefited a lot of areas (fintech and banking, retail and ecommerce, health and public transportation, marketing and advertising, security and military); between all these areas, education is one of the most important. Humans spend the majority of their time on education; education isn't just a school or university, it’s a cognitive process starting from the first days of life and lasting until the sunset. Keeping in mind that making things easier and less time-consuming is one of the biggest AI advantages and that education is one of the most time-consuming processes, it seems pretty natural that AI impact could be tremendous.”
Marcelle Bonterre is one of the Machine Learning Engineers focusing on Natural Language Processing (NLP). “Creating AI systems for use in education,” says Marcelle, “allows us to deliver on our vision like never before. Systems can now be more thorough, consider nuance, and even deliver dramatically more personalized feedback than previously possible. Fundamentally, AI is a set of mechanisms for pattern recognition. There is a popular assumption that once a pattern has been learned, an AI system should be able to judge new situations accurately. The reality we face today is managing the fact that these systems have famously amplified a lot of bad patterns learned from humans, and a few inherent to the AI techniques themselves. I appreciate the opportunity and responsibility to participate in overseeing how such systems are created and deployed in our world.”
David Adamson is passionate about leveraging AI and NLP to improve the student writing experience, especially given his background as an educator. “I began my career as a high school teacher and a learning scientist. Today, I happily mix classical NLP and state-of-the-art AI, always with the aim to help students (and their teachers) understand and respond to what's going on in their writing. This shows up in Turnitin's offerings as formative feedback, classroom analytics, and AI-assisted essay scoring,” says David. “AI-generated feedback can give students the tools to keep writing and revising in between check-ins with their instructor. Classroom insights can help an instructor pinpoint areas of improvement for their next lesson, or to guide differentiated instruction. Additionally, AI-assisted grading and feedback can lighten a teacher's workload while maintaining rigor and consistency.”
Zack Bennett has 20 years of experience building NLP, information retrieval, and machine learning solutions for legal and academic professionals. “AI helps create and improve education opportunities,” says Zack. “AI can help provide feedback during the learning process at a scale not possible with manual instruction, which improves student learning outcomes. AI can also provide meaningful insights for instructors and administrators that aid in curriculum creation, assessment, and accreditation. Finally, AI can build workflow tools that save time and resources, allowing educators to reach more students.”
Sumeet Singh is a Machine Learning Scientist specializing in Deep Learning and RL in Computer Vision and NLP. He’s dedicated his career of over 25 years to the development of Computer Science and Engineering, including AI. Sumeet appreciates AI’s “‘Deep Learning,’ also called Software 2.0, which is the latest method in AI, unlocks a whole new world of possibilities not accessible before. AI makes learning more comfortable by eliminating or ameliorating mundane and laborious tasks, so educators have more time to connect with student learning.” He hopes that “Artificial General Intelligence is achieved in his lifetime,” thus “freeing up humans to do higher-cognition tasks.” While AI provides “targeted, bespoke solutions, Artificial General Intelligence,” he says, “is more generalizable—and will be easier to apply across a wide variety of applications than the point solutions of today. That is the hope and the dream.”
Marharyta Lanhenbakh works with NLP tasks, focusing on everything concerning data: collection, verification, analysis, investigation of the best approaches to its processing and search for potential traps in every method and model application. “AI tasks give us a brilliant possibility to understand more about intelligence in general, not only artificial but human, too. We work with information, analyzing the ‘magic’ of its coding, processing, etc. While trying to teach the computer, we discover a lot about our own human cognitive and communicative processes. AI performs routine tasks and processes big amounts of data to provide data-driven insights hidden from immediate human access,” says Maryharyta.
Saurabh Bipin Chandra is a Machine Learning Scientist, focusing on leveraging AI to improve the instructor grading experience. “AI pushes the boundaries of what can be solved using traditional Computer Vision (at least making it easier!). AI can enable building tools to assist and simplify assessment creation, delivery, and grading for an instructor, thereby giving back time to instructors to focus on what they do best—educate.”
Peter Steinberg is Principal Machine Learning Software Engineer where he works on NLP models, psychometrics, exploratory data analysis, and backend engineering to support machine learning services. “I think AI helps us discover hidden patterns and new ways of looking at problems. My hope is that AI can be built into the learning experience to increase fairness, decrease bias, and make learning more efficient and enjoyable,” says Peter.
Michael Yen is a Senior Machine Learning Scientist, focusing on the application of machine learning in education technology products. “Education is a great application of AI because it can provide a better learning and instructional experience to more people for a lower cost. I believe that lowering the barrier to a high quality education is an important mission.” Michael also says he’s interested in AI because, “A fundamental restriction of traditional software engineering is that a set of predetermined rules dictate how to get from input to output. However, the world is very complex and it is impossible to have a set of rules predetermined, like what happens if the traffic light is yellow instead of red or green? Do you stop or go? AI helps solve this ambiguity by learning from real-world examples, and I think that is very exciting.”
Hanna Khanko is a Senior Machine Learning Scientist at Turnitin, where she works primarily on NLP tasks. “Every year new AI technologies revolutionize our lives,” Hanna says, “bringing new incredible solutions across a wide variety of industries. With recent breakthroughs in natural language processing and deep learning, we obtained great instruments for solving complex problems. On the other hand, we face a lot of challenges caused by them, for example, AI writing tools, which can generate high-quality text on any topic or paraphrasing tools that effectively mask plagiarism. I believe that AI can help us to detect such types of cheating and uphold academic integrity. It's great to be involved in this process and develop new solutions that will benefit people around the world.”
Leonid Voloshyn is a Machine Learning Engineer focusing primarily on NLP. “AI always surprises me,” says Leonid, “with new ways of reducing dull and manual labor for people. While we barely manage to deal with three dimensions, it doesn’t take much for a machine to analyze tons of data to provide valuable and unexpected insights. AI can make an enormous and positive impact on the educational journey. From better and more thorough integrity checks and assisting educators with the assessment process, to providing individual feedback that highlights areas for improvement.”
Ivan Bilous is a Machine Learning Software Engineer at Turnitin AI and focused on developing and supporting Turnitin services.
Finally, “At Turnitin, we believe in human-centered AI. This means putting the human user at the center of research, development, and function. We seek to build AI that assists, strengthens, and scales human abilities—not replace them. Our work with AI furthers our mission to ensure that students, educators, and institutions have the power to make data-driven decisions,” states Senior Director of Machine Learning, Eric Wang. Just as education aims to center student learning and uphold authentic voices, so does Turnitin.