Deven Desai and Mark Riedl have seen the signs for a while. 

Two years since OpenAI introduced ChatGPT, dozens of lawsuits have been filed alleging technology companies have infringed copyright by using published works to train artificial intelligence (AI) models.

Academic AI research efforts could be significantly hindered if courts rule in the plaintiffs' favor. 

Desai and Riedl are Georgia Tech researchers raising awareness about how these court rulings could force academic researchers to construct new AI models with limited training data. The two collaborated on a benchmark academic paper that examines the landscape of the ethical issues surrounding AI and copyright in industry and academic spaces.

“There are scenarios where courts may overreact to having a book corpus on your computer, and you didn’t pay for it,” Riedl said. “If you trained a model for an academic paper, as my students often do, that’s not a problem right now. The courts could deem training is not fair use. That would have huge implications for academia.

“We want academics to be free to do their research without fear of repercussions in the marketplace because they’re not competing in the marketplace,” Riedl said. 

Desai is the Sue and John Stanton Professor of Business Law and Ethics at the Scheller College of Business. He researches how business interests and new technology shape privacy, intellectual property, and competition law. Riedl is a professor at the College of Computing’s School of Interactive Computing, researching human-centered AI, generative AI, explainable AI, and gaming AI. 

Their paper, Between Copyright and Computer Science: The Law and Ethics of Generative AI, was published in the Northwestern Journal of Technology and Intellectual Property on Monday.

Desai and Riedl say they want to offer solutions that balance the interests of various stakeholders. But that requires compromise from all sides.

Researchers should accept they may have to pay for the data they use to train AI models. Content creators, on the other hand, should receive compensation, but they may need to accept less money to ensure data remains affordable for academic researchers to acquire.

Who Benefits?

The doctrine of fair use is at the center of every copyright debate. According to the U.S. Copyright Office, fair use permits the unlicensed use of copyright-protected works in certain circumstances, such as distributing information for the public good, including teaching and research.

Fair use is often challenged when one or more parties profit from published works without compensating the authors.

Any original published content, including a personal website on the internet, is protected by copyright. However, copyrighted material is republished on websites or posted on social media innumerable times every day without the consent of the original authors. 

In most cases, it’s unlikely copyright violators gained financially from their infringement.

But Desai said business-to-business cases are different. The New York Times is one of many daily newspapers and media companies that have sued OpenAI for using its content as training data. Microsoft is also a defendant in The New York Times’ suit because it invested billions of dollars into OpenAI’s development of AI tools like ChatGPT.

“You can take a copyrighted photo and put it in your Twitter post or whatever you want,” Desai said. “That’s probably annoying to the owner. Economically, they probably wanted to be paid. But that’s not business to business. What’s happening with Open AI and The New York Times is business to business. That’s big money.”

OpenAI started as a nonprofit dedicated to the safe development of artificial general intelligence (AGI) — AI that, in theory, can rival human thinking and possess autonomy.

These AI models would require massive amounts of data and expensive supercomputers to process that data. OpenAI could not raise enough money to afford such resources, so it created a for-profit arm controlled by its parent nonprofit.

Desai, Riedl, and many others argue that OpenAI ceased its research mission for the public good and began developing consumer products. 

“If you’re doing basic research that you’re not releasing to the world, it doesn’t matter if every so often it plagiarizes The New York Times,” Riedl said. “No one is economically benefitting from that. When they became a for-profit and produced a product, now they were making money from plagiarized text.”

OpenAI’s for-profit arm is valued at $80 billion, but content creators have not received a dime since the company has scraped massive amounts of copyrighted material as training data.

The New York Times has posted warnings on its sites that its content cannot be used to train AI models. Many other websites offer a robot.txt file that contains instructions for bots about which pages can and cannot be accessed. 

Neither of these measures are legally binding and are often ignored.

Solutions

Desai and Riedl offer a few options for companies to show good faith in rectifying the situation.

• Spend the money. Desai says Open AI and Microsoft could have afforded its training data and avoided the hassle of legal consequences.
  
  “If you do the math on the costs to buy the books and copy them, they could have paid for them,” he said. “It would’ve been a multi-million dollar investment, but they’re a multi-billion dollar company.”
   
• Be selective. Models can be trained on randomly selected texts from published works, allowing the model to understand the writing style without plagiarizing. 
  
  “I don’t need the entire text of War and Peace,” Desai said. “To capture the way authors express themselves, I might only need a hundred pages. I’ve also reduced the chance that my model will cough up entire texts.”
   
• Leverage libraries. The authors agree libraries could serve as an ideal middle ground as a place to store published works and compensate authors for access to those works, though the amount may be less than desired.
  
  “Most of the objections you could raise are taken care of,” Desai said. “They are legitimate access copies that are secure. You get access to only as much as you need. Libraries at universities have already become schools of information.”

Desai and Riedl hope the legal action taken by publications like The New York Times will send a message to companies that develop AI tools to pump the breaks. If they don’t, researchers uninterested in profit could pay the steepest price.

The authors say it’s not a new problem but is reaching a boiling point.

“In the history of copyright, there are ways that society has dealt with the problem of compensating creators and technology that copies or reduces your ability to extract money from your creation,” Desai said. “We wanted to point out there’s a way to get there.”

The Cloud Hub, a key initiative of the Institute for Data Engineering and Science (IDEaS) at Georgia Tech, recently concluded a successful Call for Proposals focused on advancing the field of Generative Artificial Intelligence (GenAI). This initiative, made possible by a generous gift funding from Microsoft, aims to push the boundaries of GenAI research by supporting projects that explore both foundational aspects and innovative applications of this cutting-edge technology.

Call for Proposals: A Gateway to Innovation

Launched in early 2024, the Call for Proposals invited researchers from across Georgia Tech to submit their innovative ideas on GenAI. The scope was broad, encouraging proposals that spanned foundational research, system advancements, and novel applications in various disciplines, including arts, sciences, business, and engineering. A special emphasis was placed on projects that addressed responsible and ethical AI use.

The response from the Georgia Tech research community was overwhelming, with 76 proposals submitted by teams eager to explore this transformative technology. After a rigorous selection process, eight projects were selected for support. Each awarded team will also benefit from access to Microsoft’s Azure cloud resources..

Recognizing Microsoft’s Generous Contribution

This successful initiative was made possible through the generous support of Microsoft, whose contribution of research resources has empowered Georgia Tech researchers to explore new frontiers in GenAI. By providing access to Azure’s advanced tools and services, Microsoft has played a pivotal role in accelerating GenAI research at Georgia Tech, enabling researchers to tackle some of the most pressing challenges and opportunities in this rapidly evolving field.

Looking Ahead: Pioneering the Future of GenAI

The awarded projects, set to commence in Fall 2024, represent a diverse array of research directions, from improving the capabilities of large language models to innovative applications in data management and interdisciplinary collaborations. These projects are expected to make significant contributions to the body of knowledge in GenAI and are poised to have a lasting impact on the industry and beyond.

IDEaS and the Cloud Hub are committed to supporting these teams as they embark on their research journeys. The outcomes of these projects will be shared through publications and highlighted on the Cloud Hub web portal, ensuring visibility for the groundbreaking work enabled by this initiative.

Congratulations to the Fall 2024 Winners

• Annalisa Bracco | EAS "Modeling the Dispersal and Connectivity of Marine Larvae with GenAI Agents" [proposal co-funded with support from the Brook Byers Institute for Sustainable Systems]
• Yunan Luo | CSE “Designing New and Diverse Proteins with Generative AI”
• Kartik Goyal | IC “Generative AI for Greco-Roman Architectural Reconstruction: From Partial Unstructured Archaeological Descriptions to Structured Architectural Plans”
• Victor Fung | CSE “Intelligent LLM Agents for Materials Design and Automated Experimentation”
• Noura Howell | LMC “Applying Generative AI for STEM Education: Supporting AI literacy and community engagement with marginalized youth”
• Neha Kumar | IC “Towards Responsible Integration of Generative AI in Creative Game Development”
• Maureen Linden | Design “Best Practices in Generative AI Used in the Creation of Accessible Alternative Formats for People with Disabilities”
• Surya Kalidindi | ME & MSE “Accelerating Materials Development Through Generative AI Based Dimensionality Expansion Techniques”
• Tuo Zhao | ISyE “Adaptive and Robust Alignment of LLMs with Complex Rewards”

The Energy, Policy, and Innovation Center (EPICenter) hosted the 2024 cohort of Energy Unplugged, a Science, Technology, Engineering, Art, and Math (STEAM) summer program for high school students. The weeklong camp was held at Georgia Tech’s Atlanta and Savannah campuses this summer and has earned a reputation as one of the most sought-after high-school-level summer camps hosted by Georgia Tech. 

Rich Simmons, director of Research and Studies at the Strategic Energy Institute, has been the driving force behind the camp since its inception in 2019. Simmons, a faculty instructor in the George W. Woodruff School of Mechanical Engineering at Georgia Tech, brings his award-winning teaching expertise to high school students, ensuring that each session of Energy Unplugged is both educational and engaging. The program covered a range of timely topics, from basic energy principles such as conservation laws, electric circuits, and battery storage to more complex subjects like environmental impacts, data analytics, and decision-making. In addition, students were immersed in hands-on activities, interactive demonstrations, and power plant site visits.

During the first two days, students formed teams to construct catapults and mousetrap cars, discussed the underlying physics involving energy conversion, and then launched projectiles and vehicles to test their predictions. In one of the camp’s most popular activities, students raced remote-controlled cars around an obstacle course to learn about the importance of balancing multiple objectives, such as energy use, elapsed time, safety, and cargo capacity. The week culminated in a small-group mini-project, where campers applied the skills they had acquired to solve a real-world challenge — to optimize a cooking process using solar energy. Given specific parameters on energy generation, storage, and meal demand, the students determined the best approach to convert solar energy for cooking and storage to meet a daily lunch and dinner schedule for a food truck business. The program concluded with the campers presenting their preferred designs to an audience of parents, faculty, and staff, adding public speaking and technical presentation skills to their summer experiences.

Every year, students highlight the energy field trips to power plants, data centers, robotics labs, and makerspaces as some of their favorite aspects of the camp. A student poll during the final presentations used words like fun, informative, interesting, magical, epic, exciting, educational, and fantastical to describe the camping experience. The camp introduced the students to STEM-related careers and the many undergraduate programs that could provide a pathway for them. 

Energy Unplugged provides a portal for Georgia Tech graduate student interns such as Jake Churchill and staff members such as Jordann Shields to engage students with energy concepts, activities, career paths, and information about attending Georgia Tech. 

Energy Unplugged is administered by Georgia Tech Summer P.E.A.K.S. (Program for Enrichment and Accelerated Knowledge in STEAM) at CEISMC (the Center for Education Integrating Science, Mathematics, and Computing), the primary connection point between Tech faculty and students and the K-12 STEAM education community. Annually, CEISMC programs are accessible to more than 39,000 students; 1,700 teachers; and 200 schools in over 75 school districts throughout Georgia.

As part of the Strategic Energy Institute, EPICenter taps into regional and national expertise within academia, businesses, non-governmental organizations, and research facilities to provide an unbiased and interdisciplinary framework for driving innovation in energy policy and technology in the Southeast.

A research group is calling for internet and social media moderators to strengthen their detection and intervention protocols for violent speech. 

Their study of language detection software found that algorithms struggle to differentiate anti-Asian violence-provoking speech from general hate speech. Left unchecked, threats of violence online can go unnoticed and turn into real-world attacks. 

Researchers from Georgia Tech and the Anti-Defamation League (ADL) teamed together in the study. They made their discovery while testing natural language processing (NLP) models trained on data they crowdsourced from Asian communities. 

“The Covid-19 pandemic brought attention to how dangerous violence-provoking speech can be. There was a clear increase in reports of anti-Asian violence and hate crimes,” said Gaurav Verma, a Georgia Tech Ph.D. candidate who led the study. 

“Such speech is often amplified on social platforms, which in turn fuels anti-Asian sentiments and attacks.”

Violence-provoking speech differs from more commonly studied forms of harmful speech, like hate speech. While hate speech denigrates or insults a group, violence-provoking speech implicitly or explicitly encourages violence against targeted communities.

Humans can define and characterize violent speech as a subset of hateful speech. However, computer models struggle to tell the difference due to subtle cues and implications in language.

The researchers tested five different NLP classifiers and analyzed their F1 score, which measures a model's performance. The classifiers reported a 0.89 score for detecting hate speech, while detecting violence-provoking speech was only 0.69. This contrast highlights the notable gap between these tools and their accuracy and reliability. 

The study stresses the importance of developing more refined methods for detecting violence-provoking speech. Internet misinformation and inflammatory rhetoric escalate tensions that lead to real-world violence. 

The Covid-19 pandemic exemplified how public health crises intensify this behavior, helping inspire the study. The group cited that anti-Asian crime across the U.S. increased by 339% in 2021 due to malicious content blaming Asians for the virus. 

The researchers believe their findings show the effectiveness of community-centric approaches to problems dealing with harmful speech. These approaches would enable informed decision-making between policymakers, targeted communities, and developers of online platforms.

Along with stronger models for detecting violence-provoking speech, the group discusses a direct solution: a tiered penalty system on online platforms. Tiered systems align penalties with severity of offenses, acting as both deterrent and intervention to different levels of harmful speech. 

“We believe that we cannot tackle a problem that affects a community without involving people who are directly impacted,” said Jiawei Zhou, a Ph.D. student who studies human-centered computing at Georgia Tech. 

“By collaborating with experts and community members, we ensure our research builds on front-line efforts to combat violence-provoking speech while remaining rooted in real experiences and needs of the targeted community.”

The researchers trained their tested NLP classifiers on a dataset crowdsourced from a survey of 120 participants who self-identified as Asian community members. In the survey, the participants labeled 1,000 posts from X (formerly Twitter) as containing either violence-provoking speech, hateful speech, or neither.

Since characterizing violence-provoking speech is not universal, the researchers created a specialized codebook for survey participants. The participants studied the codebook before their survey and used an abridged version while labeling. 

To create the codebook, the group used an initial set of anti-Asian keywords to scan posts on X from January 2020 to February 2023. This tactic yielded 420,000 posts containing harmful, anti-Asian language. 

The researchers then filtered the batch through new keywords and phrases. This refined the sample to 4,000 posts that potentially contained violence-provoking content. Keywords and phrases were added to the codebook while the filtered posts were used in the labeling survey.

The team used discussion and pilot testing to validate its codebook. During trial testing, pilots labeled 100 Twitter posts to ensure the sound design of the Asian community survey. The group also sent the codebook to the ADL for review and incorporated the organization’s feedback. 

“One of the major challenges in studying violence-provoking content online is effective data collection and funneling down because most platforms actively moderate and remove overtly hateful and violent material,” said Tech alumnus Rynaa Grover (M.S. CS 2024).

“To address the complexities of this data, we developed an innovative pipeline that deals with the scale of this data in a community-aware manner.”

Emphasis on community input extended into collaboration within Georgia Tech’s College of Computing. Faculty members Srijan Kumar and Munmun De Choudhury oversaw the research that their students spearheaded.

Kumar, an assistant professor in the School of Computational Science and Engineering, advises Verma and Grover. His expertise is in artificial intelligence, data mining, and online safety.

De Choudhury is an associate professor in the School of Interactive Computing and advises Zhou. Their research connects societal mental health and social media interactions.

The Georgia Tech researchers partnered with the ADL, a leading non-governmental organization that combats real-world hate and extremism. ADL researchers Binny Mathew and Jordan Kraemer co-authored the paper.

The group will present its paper at the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), which takes place in Bangkok, Thailand, Aug. 11-16 

ACL 2024 accepted 40 papers written by Georgia Tech researchers. Of the 12 Georgia Tech faculty who authored papers accepted at the conference, nine are from the College of Computing, including Kumar and De Choudhury.

“It is great to see that the peers and research community recognize the importance of community-centric work that provides grounded insights about the capabilities of leading language models,” Verma said. 

“We hope the platform encourages more work that presents community-centered perspectives on important societal problems.” 

Visit https://sites.gatech.edu/research/acl-2024/ for news and coverage of Georgia Tech research presented at ACL 2024.

A new report prepared by Regents’ Professor Marilyn A. Brown and a team of student researchers from Georgia Tech’s School of Public Policy digs into the causes of energy burden among Georgia’s Black residents. 

The study aligns with numerous other studies showing that race alone is a contributing factor to experiencing higher energy burdens. However, the Georgia Tech research findings include data showing that homes with children, older people, or those headed by women were even more at risk. Researchers also found that a 13% increase in an area’s Black population equated to an approximately 1% increase in energy burden. 

Households are often considered energy-burdened if they spend more than 6% of their monthly budget on energy, according to the report. 

“One thing that sets this Sierra Club report aside from other breakdowns of energy burden across the country is the meticulous description of the conditions and causes of high energy burdens among 33 energy-stressed Black households in Georgia, who were identified and interviewed by community organizations,” Brown said. 

Historical trends such as mortgage redlining, highway, and power plant placements, and the effect of deforestation and urban heat islands on urban, predominantly Black communities all play a role in contributing to the unusually high energy costs many Black Georgians end up paying, according to the report. 

“This isn’t an abstract thing. People are having to choose whether they cool their homes or put food on the table or buy medicine,” said Brown, also Brook Byers Professor of Sustainable Systems. 

While the report—parts of which have been published in a peer-reviewed journal and another manuscript under review—makes no policy recommendations, the researchers note that changes to state and federal housing policies are urgently needed. 

“Implementing effective policy solutions would not only decrease high energy burdens, bill payment problems, and utility shut-offs, but would also promote the health, safety, and economic vitality of Black families, slash U.S. carbon emissions and build a stronger, more inclusive climate movement,” they wrote. 

The report, Energy Burdens of Black Households in Georgia” was published on March 14 by the Sierra Club, which funded the research. 

In addition to Brown, Ph.D. students Snehal Kale, Ryan Anthony, and Majid Ahmadi, and alum Ashley Hill, MSEEM 2022, co-authored the report. 

A new study by Associate Professor Omar Isaac Asensio and a team of students in Georgia Tech’s School of Public Policy finds that federal housing policies accelerate energy efficiency participation among low- and moderate-income households — even when those policies don’t directly address energy efficiency. 

The research, published in Nature Sustainability, shows how community development block grants from the U.S. Department of Housing and Urban Development (HUD) generated an average of 5% to 11% energy savings in economically burdened households in Albany. The savings equate to the cost of roughly two months of groceries per household per year. 

"These housing participants who didn't come in thinking about energy efficiency saved anywhere from $75 to $482 per year in energy bills," Asensio said. "Those are meaningful savings that really impact people. So, we ended up finding very significant hidden social benefits from these policies that were previously unknown." 

https://youtu.be/eWqOFj9qRxw

The findings are surprising because HUD grants do not specifically target energy efficiency or sustainability measures in exchange for governmental assistance. Instead, they are given at the discretion of the local government to residents facing housing emergencies such as deteriorating roofs or broken HVAC systems in the hot summer. Because of the high amount of deferred maintenance in these homes, the fixes have a spillover effect of significantly reducing energy use — for example, by adopting more efficient technologies and bringing structures up to building codes — and saving money for people who receive them.  

The multidisciplinary research team in Asensio’s Data Science & Policy Lab, including current and former Public Policy students Olga Churkina and Becky D. Rafter and industrial engineering alumna Kira E. O'Hare, also found that the cost-effectiveness of housing-based interventions rivals standalone energy efficiency policies, offering a promising alternative for reaching marginalized communities.  

"For decades, we’ve struggled to get meaningful participation with conventional policies in these lower and moderate-income communities, including among renters and people in multi-family homes,” Asensio said. "Using housing block grants as an entry strategy to drive efficiency is an important policy innovation.” 

With support from the National Science Foundation, ESRI, Inc., and the Georgia Smart Communities Challenge, Asensio and his co-authors spent nearly four years collecting, cleaning, and combining Albany's previously siloed city data into one community analytics repository. They linked records for 5.9 million utility bills per month from 2004 to 2019, allowing them to see long-run impacts of policy intervention, energy consumption, and payments by household — an uncommonly granular level of data.  

"Overall, HUD-funded block grants in Albany reduced electricity use by 4.72 million kilowatt hours over the study period versus the control group," the researchers wrote. "The reduction in non-baseload emissions is equivalent to 3.70 million pounds of coal not being burned or the carbon sequestered by 3,695 acres of forest." 

Asensio's research is timely because the Southeast has some of the country's highest energy-burdened households. In the U.S., spending over 6% of net income on energy is considered a burden. In Albany, renters' and homeowners' energy costs can surpass ten or even 20% of household budgets, Asensio said, and many housing applicants are elderly and on fixed incomes.  

Unlike conventional energy initiatives that are reliant on self-selection, housing programs can provide a more equitable and localized strategy. That's because "most of the standalone policies for energy efficiency have two main outcomes," Asensio said. "First, the programs generally attract more affluent and informed homeowners, in which case, questions arise as to whether this might be a good use of public funds. Second, when these policies are restricted to certain income eligibility limits, we don't get enough participation from lower-income residents for a long list of reasons. So, reaching low- and moderate-income households has become a fundamental challenge." 

In contrast, housing block grants naturally target a broader range of residents with high energy burdens and help circumvent the problem of low participation. Rather than trying to market an energy-saving offer to people who aren't interested or are distrustful of the government, HUD grants have long waiting lists.  

"There are thousands and thousands of communities that look very much like Albany within and outside of major metro areas,” Asensio said. "This is a relatively untapped opportunity for driving energy efficiency within households who may not necessarily have an awareness of or interest in energy efficiency measures.”  

The paper, “Housing Policies and Energy Efficiency Spillovers in Low and Moderate Income Communities,” was published online in Nature Sustainability on March 18. It is available at https://doi.org/10.1038/s41893-024-01314-w. This work was partially supported by awards from the National Science Foundation (Award No. 1945332), ESRI, Inc., the Georgia Smart Communities Challenge, and the Institute for the Study of Business in Global Society at Harvard Business School. 

Hyundai Motor Group Innovation Center Singapore hosted the Meta-Factory Conference Jan. 23 – 24. It brought together academic leaders, industry experts, and manufacturing companies to discuss technology and the next generation of integrated manufacturing facilities.

Seth Hutchinson, executive director of the Institute for Robotics and Intelligent Machines at Georgia Tech, delivered a keynote lecture on “The Impacts of Today’s Robotics Innovation on the Relationship Between Robots and Their Human Co-Workers in Manufacturing Applications” — an overview of current state-of-the-art robotic technologies and future research trends for developing robotics aimed at interactions with human workers in manufacturing.

In addition to the keynote, Hutchinson also participated in the Hyundai Motor Group's Smart Factory Executive Technology Advisory Committee (E-TAC) panel on comprehensive future manufacturing directions and toured the new Hyundai Meta-Factory to observe how digital-twin technology is being applied in their human-robot collaborative manufacturing environment.

Hutchinson is a professor in the School of Interactive Computing. He received his Ph.D. from Purdue University in 1988, and in 1990 joined the University of Illinois Urbana-Champaign, where he was professor of electrical and computer engineering until 2017 and is currently professor emeritus. He has served on the Hyundai Motor Group's Smart Factory E-TAC since 2022.

Hyundai Motor Group Innovation Center Singapore is Hyundai Motor Group’s open innovation hub to support research and development of human-centered smart manufacturing processes using advanced technologies such as artificial intelligence, the Internet of Things, and robotics.

- Christa M. Ernst

Related Links

• Hyundai Newsroom Article: Link
• Event Link: https://mfc2024.com/
• Keynote Speakers: https://mfc2024.com/keynotes/