Almost 400,000 babies were born prematurely—before 37 weeks gestation—in 2018 in the United States. One of the leading causes of newborn deaths and long-term disabilities, preterm birth (PTB) is considered a public health problem with deep emotional and challenging financial consequences to families and society. If doctors were able to use data and artificial intelligence (AI) to predict which pregnant women might be at risk, many of these premature births might be avoided.
IBM has selected assistant professor Baishakhi Ray for an IBM Faculty Award. The highly selective award is given to professors in leading universities worldwide to foster collaboration with IBM researchers. Ray will use the funds to continue research on artificial intelligence-driven program analysis to understand software robustness.
Although much research has been done, there are still countless vulnerabilities that make system robustness brittle. Hidden vulnerabilities are discovered all the time – either through a system hack or monitoring system’s functionalities. Ray is working to automatically detect system weaknesses using artificial intelligence (AI) with her project, “Improving code representation for enhanced deep learning to detect and remediate security vulnerabilities”.
One of the major challenges in AI-based security vulnerability detection is finding the best source code representation that can distinguish between vulnerable versus benign code. Such representation can further be used as an input in supervised learning settings for automatic vulnerability detection and fixes. Ray is tackling this problem by building new machine-learning models for source code and applying machine learning techniques such as code embeddings. This approach could open new ways of encoding source code into feature vectors.
“It will provide new ways to make systems secure,” said Ray, who joined the department in 2018. “The goal is to reduce the hours of manual effort spent in automatically detecting vulnerabilities and fixing them.”
A successful outcome of this project will produce a new technique to encode source code with associated trained models that will be able to detect and remediate a software vulnerability with increased accuracy.
They could have been at the beach enjoying the summer. Instead, high school students gathered from across New York City and New Jersey for the AI4All program hosted by the Columbia community. The students came to learn about artificial intelligence (AI) but this program had a special twist – computer science (CS) and social work concepts were combined for a deeper, more meaningful look at AI.
“We created a space for young people to think critically about the social implications of artificial intelligence for the communities that they live in,” said Desmond Patton, the program co-director and associate professor of the School of Social Work. “We wanted them to understand how things like race, power, privilege and oppression can be baked into algorithms and their adverse effects on communities.”
The program participants, composed of 9th, 10th and 11th graders, are from racial and ethnic groups underrepresented in AI: Black, Hispanic, and Asian. Girls as well as youth from lower-income backgrounds were particularly encouraged to apply. For three weeks the students attended lectures, went on field trips to visit local companies (LinkedIn and Samsung) involved in the program, and visited other AI4All programs, like at Princeton University. Their work culminated in a final project which they presented to their classmates, mentors, and industry professionals.
“I believe that it is important to bring more ethics to AI,” said Augustin Chaintreau, the program co-director and a CS assistant professor. He sees ethics integrated into technical concepts and taught at the same time. Instead of learning about the social consequences and fixing it after, to solve an issue. Shared Chaintreau, “It shouldn’t be thought about just in passing but as a central part of why this is a tool and its implications.”
An interdisciplinary approach to AI was even part of how the classes were structured. Technical CS concepts, such as machine learning and Python, were taught in the morning by professors and student volunteers. While in the afternoon, guest speakers came to talk about their perspective to the day’s lesson. So, on the same day, students learned about supervised and unsupervised learning, and in the afternoon, someone who was formerly incarcerated described how the criminal policing that survey people on social media had a role in making a case against them.
“We were learning college courses meant to be taught in a month but for us it was just a couple of weeks and that was really impressive,” said Genesis Lopez, who is part of the robotics team at her school. Lopez loves robotics but works more on the mechanical side. She goes back to the team knowing how to use Python and is confident she can step up and code if needed. Continued Lopez, “I learned a lot but my favorite part was the people, we became a family.”
Kai-Fu Lee (B.S. ’83) included in WIRED’s anniversary issue for his work that brings humanity to artificial intelligence.
Artificial intelligence (AI) has seeped into the daily lives of people in the developed world. From virtual assistants to recommendation engines, AI is in the news, our homes and offices. There is a lot of untapped potential in terms of AI usage, especially in humanitarian areas. The impact could have a multiplier effect in developing countries, where resources are limited. By leveraging the power of AI, businesses, nongovernmental organizations (NGOs) and governments can solve life-threatening problems and improve the livelihood of local communities in the developing world.