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Neural architecture search (NAS) is a promising research direction that has the potential to replace expert-designed networks with learned, task-specific architectures. In this work, in order to help ground the empirical results in this field, we propose new NAS baselines that build off the...

Inferring a person's goal from their behavior is an important problem in applications of AI (e.g. automated assistants, recommender systems). The workhorse model for this task is the rational actor model - this amounts to assuming that people have stable reward functions, discount the future...

In order for artificial agents to coordinate effectively with people, they must act consistently with existing conventions (e.g.how to navigate in traffic, which language to speak, or how to coordinate with teammates). A group’s conventions can be viewed as a choice of equilibrium in a coordination...

Although algorithmic auditing has emerged as a key strategy to expose systematic biases embedded in software platforms, we struggle to understand the real-world impact of these audits, as scholarship on theimpact of algorithmic audits on increasing algorithmic fairness and transparency in...

Client-side indecent content checking
A simple JavaScript library to help you quickly identify unseemly images; all in the client's browser. NSFWJS isn't perfect, but it's pretty accurate (~90% from our test set of 15,000 test images)... and it's getting more accurate all the time.

In today’s competitive environment, innovation is indispensable, but it is not enough.

Having a sense of self lies at the heart of what it means to be human. Without it, we couldn’t navigate, interact, empathise or ultimately survive in an ever-changing, complex world of others. We need a sense of self when we are taking action, but also when we are anticipating the consequences of…

Artificial intelligence researchers and engineers have spent a lot of effort trying to build machines that look like humans and operate largely independently. Those tempting dreams have distracted many of them from where the real progress is already happening: in systems that enhance – rather than…

For several years, scholars have (for good reason) been largely preoccupied with worries about the use of artificial intelligence and machine learning (AI/ML) tools to make decisions about us. Only recently has significant attention turned to a potentially more alarming problem: the use of AI/ML to...

While formal definitions of fairness in machine learning (ML) have been proposed, its place within a broader institutional model of fair decision-making remains ambiguous. In this paper we interpret ML as a tool for revealing when and how measures fail to capture purported constructs of interest...

Reinforcement learning is a promising framework for solving control problems, but its use in practical situations is hampered by the fact that reward functions are often difficult to engineer. Specifying goals and tasks for autonomous machines, such as robots, is a significant challenge...

Developing countries must begin seriously considering how technological changes will impact labour trends.

How will each drug interact with the proteins in your body?

The U.S. may be ahead for now, but not by much.

There is and has been a fruitful flow of concepts and ideas between studies of learning in biological and artificial systems. Much early work that led to the development of reinforcement learning (RL) algorithms for artificial systems was inspired by learning rules first developed in biology by Bush...

One way to interpret neural model predictions is to highlight the most important input features---for example, a heatmap visualization over the words in an input sentence. In existing interpretation methods for NLP, a word's importance is determined by either input perturbation---measuring the...

Gaining a better understanding of how and what machine learning systems learn is important to increase confidence in their decisions and catalyze further research. In this paper, we analyze the predictions made by a specific type of recurrent neural network, mixture density RNNs (MD-RNNs). These...

Sometimes the questions become too much for artificial intelligence systems

I can still recall my surprise when a book by evolutionary biologist Peter Lawrence entitled “The making of a fly” came to be priced on Amazon at $23,698,655.93 (plus $3.99 shipping). While my colleagues around the world must have become rather depressed that an academic book could achieve such a…

Are you ready for artificial intelligence in schools?

You may already know that researchers believe AI is likely to predict the onset of diseases in future
and that you’re already using AI every day when you search online, use voice commands on your phone or use Google Translate.

Maybe you heard…