Shapley values underlie one of the most popular model-agnostic methods within explainable artificial intelligence. These values are designed to attribute the difference between a model's prediction and an average baseline to the different features used as input to the model. Being based on solid game-theoretic principles, Shapley values uniquely satisfy several desirable properties, which is why they are increasingly used to explain the predictions of possibly complex and highly non-linear machine learning models. Shapley values are well calibrated to a user's intuition when features are independent, but may lead to undesirable, counterintuitive explanations when the independence assumption is violated. In this paper, we propose a novel framework for computing Shapley values that generalizes recent work that aims to circumvent the independence assumption. By employing Pearl's do-calculus, we show how these'causal' Shapley values can be derived for general causal graphs without sacrificing any of their desirable properties. Moreover, causal Shapley values enable us to separate the contribution of direct and indirect effects. We provide a practical implementation for computing causal Shapley values based on causal chain graphs when only partial information is available and illustrate their utility on a real-world example.

Breakthroughs, discoveries, and DIY tips sent every weekday. Mitsubishi's bragging rights for designing the world's fastest Rubik's cube-solving robot have officially been stolen by a team of undergrads in Indiana. Earlier this month, Purdue University announced four collaborators in its Elmore Family School of Electrical and Computer Engineering (ECE) successfully designed and built a bot that not only set the new Guinness World Record--it absolutely demolished the multinational company's previous time. Meet Purdubik's Cube: a machine capable of completing a randomly shuffled Rubik's cube in just 0.103 seconds. At 1-2 times faster than the blink of a human eye, the feat is difficult to see, much less comprehend.

Within seconds, you've been scanned, stored, and tracked--before even reaching airport security. Without ever handing over your ID, the Transportation Security Administration (TSA) already knows exactly who you are. This is happening at 84 airports across the US. And chances are, you didn't even notice. Marketed as a tool to enhance security, TSA's facial recognition system is drawing criticism for its potential to track Americans from the terminal entrance to their final destination.

Good Job is Slate's advice column on work. Have a workplace problem big or small? I am a hard-line hater of generative AI (ChatGPT, Midjourney, etc.). I think it's bad for the environment and bad for society. It burns water resources, exploits workers in the global south, plagiarizes art and writing, and eliminates badly needed entry-level jobs.

The supplementary material consists of the following. Additional Results of the DomainNet dataset for 5 and 10-shot settings with Resnet34 as backbone network are shown in Table 1. Results are reported in Tables 2 and 3 Discussion on Limitations and Societal Impacts. The architecture of the network is similar to [2]. All other hyperparameters used in our framework are described in the main paper.

In an AI-powered economy, data security is not just a box-checking exercise. Instead, security is the catalyst for trust and innovation within your organization and with your customers. That's the conclusion from the State of IT report from Salesforce, which surveyed over 4,000 IT decision-makers worldwide, including more than 2,000 professionals specializing in security, privacy, or compliance. The survey aimed to understand fast-evolving cyber threats and security priorities, suggesting how to build customer trust in an AI-driven world and use AI to improve security postures. According to the State of IT survey, the top five most concerning security threats are cloud security, data poisoning, malware, phishing, and ransomware. The top five most effective security tactics are data encryption, data backup and restore, identity and access management, zero-trust strategies, and data masking.