Artificial intelligence is literally everywhere today, whether we realize it or not. How many of us have been fooled into thinking a video or photo was real, only to find out it was generated by an AI? Or maybe you ask Google a question, get an answer from the AI, and wonder, “Should I believe the answer or keep looking?”
Iowa State University College of Arts and Sciences (LAS) faculty are at the forefront of the AI technology revolution, developing computational solutions, quantifying the statistical certainty of AI output, and exploring how AI can enable new inventions and innovations.
Importantly, LAS academics and researchers are also studying the ethical implications and trustworthiness of AI, which has sparked a new initiative called Trusted Innovation in AI.
Applying the unique strengths of LAS to AI
The Trusted Innovation in AI initiative focuses primarily on research that builds on LAS’ strengths in trustworthy, ethical, and interdisciplinary AI. The university is also considering broader AI initiatives, including integrating AI into the curriculum and establishing policies on how to implement AI in the classroom.
“Our faculty in the College of Liberal Arts and Sciences are uniquely positioned to lead research into trustworthiness in artificial intelligence because we frame the challenge of generative AI from the perspective that it is not just technical, but fundamentally human,” said LAS Dean Benjamin Withers. “Our strengths across the humanities, social sciences, mathematics, and natural sciences allow us to simultaneously examine AI through the lenses of ethics, communication, policy, human behavior, and scientific rigor. By integrating these disciplines, we can ensure that AI systems are not only innovative, but also transparent, accountable, and worthy of public trust.”
Within the Iowa State University AI ecosystem, LAS scholars contribute expertise to develop computing solutions, quantify the statistical certainty of AI output, explore how AI enables new discoveries and innovations, and study the ethical and social implications of AI.
The goal of LAS is not only to create new AI applications, but also to ensure that those applications are trustworthy and ethical.
The need for trust and ethics in AI
A common complaint about AI is something called hallucinations. This is information generated by an AI model that sounds true and achievable, but is actually false and inaccurate.
“Many of the people working on the fundamentals of AI, including statisticians, the Center for Research and Statistics Methodology, and computer science, are interested in knowing when the answer is right.
Another element of AI reliability is determining how the model comes up with answers to questions.
“Another aspect is explainability,” said Geetu Tuteja, interim associate dean for strategic research initiatives at LAS. “People need to understand how AI systems arrive at their answers and what data and inferences influenced those results.”
Closely tied to AI trustworthiness is ethics. Revolutionary advances in the technical aspects of AI are exciting, but when does it go too far? For example, the news is full of examples of artists’ portraits being used without their permission. There’s also the reality of AI’s impact on the environment. How will the growth of AI impact sustainability concerns?
“LAS is uniquely positioned to approach AI from multiple perspectives, with researchers studying everything from its technical foundations and applications to its ethical, political, and human dimensions,” Tuteya said. “That breadth allows us to consider not only what AI can do, but also how AI should be used responsibly.”
solid foundation
In recent years, LAS has developed AI projects with a focus on trust and ethics, as well as creating new AI development opportunities for students. This work, detailed below, will form the basis for future projects related to the Trusted Innovation in AI initiative.
- Researchers at the Center for Research Statistics and Methodology are developing AI-assisted methods to support the National Resource Inventory (NRI), a nationwide program that monitors the status of land use and natural resources across the United States. This project uses advanced AI and computer vision techniques to detect changes in land cover and land use categories from high-resolution imagery while quantifying the uncertainty in AI predictions.
- The Department of Computer Science’s new minor in Applied AI will teach undergraduates how to use AI to address real-world challenges. Students will also explore the social impacts, ethical considerations, and potential challenges associated with AI.
- The Master of Science in AI, offered through the Department of Computer Science, provides graduate students with a deeper understanding of AI and machine learning. This degree helps students apply AI to important global challenges.
- The Dependable Data-Driven Discovery (D4) program is an interdisciplinary research and training initiative focused on ensuring rigorous quality assurance for data-driven and AI discovery derived from biological and other data sources. Graduate students can apply for traineeships and undergraduate students can apply for assistantships to learn about data science fundamentals, methodologies, and tools to generate trusted, data-driven discoveries.
future funding
New projects related to the Trusted Innovation in AI initiative are underway and will be launched as soon as funding is available. New financial support will also help facilitate joint workshops and future ideas.
Currently, most of Trusted Innovation’s work in AI initiatives is funded by private donors in the form of named professorships. AI-related professorships currently held by LAS faculty include:
- Peng Liu, Professor of Statistics and Lawrence H. Baker Professor of Biological Sciences
- Carol Chappelle, Professor of English, Distinguished Professor, LAS Dean’s Professor
- Wallapak Tavanapong, Professor of Computer Science and Kingland Systems Professor of Data Analysis and Cognitive Machine Learning
- Myra Cohen, Professor of Computer Science; Lan and Oanh Nguyen, Professor of Software Engineering
- Zhengyuan Zhu, Professor of Statistics, Kingland Systems Fellow in Data Analytics and Cognitive Machine Learning, Director of the Center for Survey Statistics and Methodology, and Co-Director of the ISU Federal Statistical Research Data Center
Tuteja has spearheaded this collaborative movement and recently organized a luncheon to connect LAS faculty interested in developing AI partnerships. LAS faculty who would like to participate in future events or find partners for new AI projects should contact Tuteja at geetu@iastate.edu.
“We see this as a seed for something bigger,” McIntosh said. “We bring them together, help them connect, and provide support for leadership.”
