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"These types of projects can open the eyes of the community to the extensive potential that lies within responsible AI," Mazzolenis said.

Isabella Bossas team worked with the Nature Conservancy to build computer vision algorithms to perform species classification and anomaly detection on images from camera traps set up in coastal ecosystems in California, training the models on approximately 100,000 images. Other conservation projects looked at species detection algorithms and mapping agricultural plastic use in California.

Its not something I wouldve envisioned if the Capstone hadnt partnered us with the Nature Conservancy. It really broadened my perspective, Bossa said. Its a very positive outlook for the future of AI research. There have been so many concerns about what AI can do, its potential downsides. But these projects show that AI can be used for good.

Frontline Negotiation is an international organization for negotiators that work to bring humanitarian aid to regions in need. Several SEAS groups worked with the organization to develop tools negotiators could use to more quickly learn all the different stakeholder groups involved in a specific situation or crisis.

Stakeholder mapping is a modular procedure used by frontline negotiators to identify all the stakeholders, and then based on all available information and contextual knowledge, a frontline negotiator will map the stakeholders into four quadrants, said Boxiang Wang. Our tools automate that process to achieve really accurate and fascinating results. That drastically reduces the time spent by the human expert, and the AI can also suggest a strategy based on the mapping. The negotiator can then utilize the tools weve created to assist in their decision-making.

Because AI research relies on accurate data sets, several teams researched data resiliency and security. New vision language models like OpenAIs GPT4, for example, can take data from images as well as text, so Frank Lis team researched how to prevent adversarial attacks from bad visual inputs. Kirsten Morehouses team looked at data security from the perspective of equity, researching guidelines to help ensure fair, representative, and private datasets, especially in healthcare.

There have been a lot of campaigns recently about data privacy, so we thought it was the right time to research it, Morehouse said. With the advent and use of so many new, powerful algorithms, ensuring that training data is both fair and private is a priority.

Norman added, At the end of the day, machine learning is really dependent on data quality. If you dont have good data quality, you cant do good machine learning research.

The data science program is a three-semester masters degree jointly led by the Computer Science and Statistics faculties. AC297R is also taken by undergraduates pursuing concurrent masters degrees, as well Ph.D. students taking a secondary concentration in computation or getting a Master of Science degree en route to the Ph.D. Some of this past semesters 297R cohort will be extending their program into the spring to continue researching these topics.

Im super proud of them, Pan said. This is really an entirely project-based course. This is a simulated internship. The students really had to work on every aspect of professional conduct, not just applying the math and computation.

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Innovating new spaces with AI - Harvard School of Engineering and Applied Sciences