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Steven Skiena

This graphic summarizes shifts in public attitudes about AI, according to the Stony Brook-led survey. Image by Jason Jones

A Stony Brook University study suggests that on average, U.S. adults have gained confidence in the capabilities of AI and grown increasingly opposed to extending human rights to advanced AI systems.

In 2021, two Stony Brook University researchers – Jason Jones, PhD, Associate Professor in the Department of Sociology, and Steven Skiena, PhD, Distinguished Teaching Professor in the Department of Computer Science – began conducting a survey study on attitudes toward artificial intelligence (AI) among American adults. Some of their recent findings, published in the journal Seeds of Science, show a shift in Americans’ views on AI.

The researchers compared data collected from random, representative samples in 2021 and 2023 to determine whether public attitudes toward AI have changed amid recent technological developments – most notably the launch of OpenAI’s ChatGPT chatbot in late 2022. The new work builds on previous research into how AI is perceived in society, by way of the Jones-Skiena Public Opinion of Artificial Intelligence Dashboard and similar survey studies conducted with varying demographics.

The new study sampled two unique groups of nearly 500 Americans ages 18 and above, one of which was surveyed in March 2021 and the other in April 2023. Participants shared their opinions on the achievability of constructing a computer system able to perform any intellectual task a human is capable of, whether such a system should be built at all, and/or if that system – referred to as Artificial General Intelligence (AGI) – should be afforded the same rights as a human being.

Google Surveys was originally used as the platform for this research due to its capability of delivering random, representative samples.

“What we truly wanted to know was the distribution and average of public opinion in the U.S. population,” says Jones, co-author and also a member of Stony Brook’s Institute for Advanced Computational Science (IACS). “A random, representative sample is the gold standard for estimating that in survey research. Google shut down their Google Surveys product in late 2022, so we used another platform called Prolific to do the same thing for the second sample.”

Once the samples were collated, a statistically significant change in opinion was revealed regarding whether an AGI system is possible to build and whether it should have the same rights as a human.

In 2023, American adults more strongly believed in the achievability of AGI, yet were more adamantly against affording such systems the same rights as human beings. There was no statistically significant change in public opinion on whether AGI should be built, which was weakly favored across both samples.

Jones and Skiena stress that more studies must be conducted to better understand public perceptions of artificialintelligence as the technology continues to grow in societal relevance.

They will repeat the survey this spring with the same methods used in 2023 with the hope of  building further on their findings.

From left, graduate students Prakhar Avasthi, Alisa Yurovsky, Charuta Pethe and Haochen Chen with director Steven Skiena, center. Photo by Gary Ghayrat/Stony Brook University

By Daniel Dunaief

Steven Skiena practices what he teaches. Named the director of the Institute for AI-Driven Discovery and Innovation in the College of Engineering and Applied Sciences at Stony Brook University, Skiena is using artificial intelligence to search for three staff members he hopes to hire in this new initiative.

He is looking for two tenured professors who will work in the Department of Computer Science and one who will be a part of the Department of Biomedical Informatics.

“We hope to use an artificial intelligence screen,” which Skiena calls a Poach-o-matic to “identify candidates we might not have thought of before. Ideally, the program will kick up a name and afterward, we’d bump our hand on our head and say, ‘Of course, this person might be great.’”

Steven Skiena. Photo from SBU

Artificial intelligence and machine learning have become popular areas in research institutions like Stony Brook, as well as in corporations with a wide range of potential applications, including in search engine companies like Google.

Skiena, who is a distinguished teaching professor, said he has “several candidates and we’re now actively interviewing,” adding that many departments on campus have faculty who are interested in applying machine learning in their work.

“There’s been an explosion of people from all disciplines who are interested in this,” Skiena said. He recently met with a materials scientist who uses machine learning techniques to improve experimental data. He’s also talked with people from the business school and from neuroscience.

SBU students have also shown considerable interest in these areas. Last semester, Skiena taught 250 graduate students in his introduction to data science class.

“This is a staggering demand from students that are very excited about this,” he said. Machine learning has become a “part of the standard tool kit for doing mathematical modeling and forecasting in many disciplines and that’s only going to increase.”

In an recent email, Andrew Schwartz, a core faculty at the institute and an assistant professor in the Department of Computer Science at Stony Brook, said he believes bringing in new faculty “should attract additional graduate students that may become future leaders in the field.”

Increasing coverage of AI beyond the current expertise in vision, visualization, natural language processing and biomedical engineering can “go a long way. There are a large amount of breakthroughs in AI that seemingly come from taking an idea from one subfield and applying it to another.” Schwartz appreciates the impact Skiena, who is his faculty mentor, has had on the field.

Skiena has “managed to contribute to a wide range of topics,” Schwartz explained. His book, “The Algorithm Design Manual,” is used by people worldwide preparing for technical interviews. Knowing this book thoroughly is often a “suggested step” for people preparing to interview at Google or other tech companies, Schwartz added.

The students in Schwartz and Skiena’s labs share space and have regular weekly coffee hours. Schwartz appreciates how Skiena often “presents a puzzling question or an out-of-the-box take on a question.”

The core technical expertise at the institute is in machine learning, data science, computer vision and natural language processing.

The creation of the institute shows that Stony Brook is “serious about being one of the top universities and research centers for expertise in AI,” explained Schwartz.

A few years ago, researchers realized that the artificial intelligence models developed biases based on the kind of training data used to create them. “If you’re trying to build a system to judge resumes to decide who will be a good person to hire for a certain type of job” the system has a danger of searching for male candidates if most or all of the people hired had been male in the past, Skiena explained.

Unintentional biases can creep in if the data sets are skewed toward one group, even if the programmer who created the artificial intelligence system was using available information and patterns.

In his own research, Skiena, who has been at Stony Brook since 1988, works on natural language processing. Specifically, he has explored the meaning of words and what a text is trying to communicate.

He has worked on sentiment analysis, trying to understand questions such as whether a particular political figure who receives considerable media coverage is having a good or bad week.

Another project explores the quality of news sources. “Can you algorithmically analyze large corpuses of news articles and determine which are reliable and which are less so?” he asked. 

One measure of the reliability of a news source is to determine how much other articles cite from it. “It is important to teach skepticism of a source” of news or of data, Skiena said. 

“When I teach data science, a lot of what I teach includes questions of why you believe a model will do a good thing and why is a data source relevant,” he added.

A resident of Setauket, Skiena lives with his wife Renee. Their daughter Bonnie is a first-year student at the University of Delaware, where she is studying computer science. Their tenth-grade daughter Abby attends Ward Melville High School and joins her father for bike rides on Long Island.

Skiena, who grew up in East Brunswick, New Jersey, said he appreciates the university community. By working in the AI field, Skiena, who has seven doctoral students in his lab, said he often observes glitches in online models like article classification on Google News or advertisements selected for him on a website to try to figure out why the model erred. He has also developed a sense of how probability and random events work, which he said helps him not overinterpret unusual events in day-to-day life.

As for his work at the institute, Skiena hopes Stony Brook will be recognized as a major player in the field of machine learning and areas of artificial intelligence. “We have good faculty in this area already and we’re hiring more. The hope is that you reach critical mass.”