Evaluating similarity of visual art from both human perceptual & quantitative judgments — Similarity-based image search, also known as content-based image retrieval, has historically been a challenging computer vision task. This problem is especially difficult for visual art, because it is less obvious as to what a metric of “similarity” should be defined as and who should set that standard for art.

How do AI algorithms fit into recidivism prediction and criminal justice going forward? — For the second episode of our interview series with AI experts, we welcome Julia Dressel! Julia Dressel is a current software engineer at Recidiviz, a technical nonprofit organization that provides tools and infrastructure to improve the criminal justice system. She previously has worked for Apple and graduated from Dartmouth with…

Building a web application that transforms photographs into artworks of one’s chosen style — This article was produced as part of the final project for Harvard’s AC215 Fall 2021 course. This project consists of team members Benjamin Wu, Catherine Yeo, and Zev Nicolai-Scanio. Introduction When planning their artwork, artists often have difficulty deciding the style or visualizing the final piece of artwork they want to…

How can we better design responsible AI and technology? — For the first episode of our long-awaited interview series with AI experts, we’re super excited and honored to chat with Shalaleh Rismani. Shalaleh is currently the co-director and a design researcher at the Open Roboethics Institute (ORI), a Canadian think tank investigating the ethical and social implications of AI and…

A technique to explain how black-box machine learning classifiers make predictions — It’s needless to say: machine learning is powerful. At the most basic level, machine learning algorithms can be used to classify things. Given a collection of cute animal pictures, a classifier can separate the pictures into buckets of ‘dog’ and ‘not a dog’. …

A guide for college students on factors to consider and options for what to do in the next school year — In the last month, many US universities have announced their fall reopening plans. Some universities have proposed a hybrid model, with some students returning to campus for in-person classes and others staying home, or offering a select number of small classes being held in-person. …

Why many gold-standard computer vision datasets, such as ImageNet, are flawed — Even though it was created in 2009, ImageNet is the most impactful dataset in computer vision and AI today. Consisting of more than 14 million human-annotated images, ImageNet has become the standard for all large-scale datasets in AI. …

Papers, books, and resources to learn about fairness in vision, NLP, and more — Recent discussion in the machine learning community has brought to light the importance and necessity of understanding not just machine learning, but all the considerations of bias and fairness behind every algorithm’s usage. “This isn’t a call for ‘diversity’ in datasets or ‘improved accuracy’ in performance — it’s a call…

An overview of how to use counterfactual fairness to quantify the social bias of crowd workers — Crowdsourcing is widely used in machine learning as an efficient form of annotating datasets. Platforms like Amazon Mechanical Turk allow researchers to collect data or outsource the task of labelling training data from individuals all over the world. However, crowdsourced datasets often contain significant social biases, such as gender or…