AI alignment refers to models acting towards human-intended goals, preferences, or ethical principles. Analyzing the similarity between models and humans can be a proxy measure for ensuring AI safety. In this paper, we focus on the models' visual perception alignment with humans, further referred to as AI-human visual alignment. Specifically, we propose a new dataset for measuring AI-human visual alignment in terms of image classification. In order to evaluate AI-human visual alignment, a dataset should encompass samples with various scenarios and have gold human perception labels. Our dataset consists of three groups of samples, namely Must-Act (i.e., Must-Classify), Must-Abstain, and Uncertain, based on the quantity and clarity of visual information in an image and further divided into eight categories. All samples have a gold human perception label; even Uncertain (e.g., severely blurry) sample labels were obtained via crowd-sourcing. The validity of our dataset is verified by sampling theory, statistical theories related to survey design, and experts in the related fields. Using our dataset, we analyze the visual alignment and reliability of five popular visual perception models and seven abstention methods.

AI alignment refers to models acting towards human-intended goals, preferences, or ethical principles. Analyzing the similarity between models and humans can be a proxy measure for ensuring AI safety. In this paper, we focus on the models' visual perception alignment with humans, further referred to as AI-human visual alignment. Specifically, we propose a new dataset for measuring AI-human visual alignment in terms of image classification. In order to evaluate AI-human visual alignment, a dataset should encompass samples with various scenarios and have gold human perception labels.

Either it is a master or a servant. And there are two kinds of relationships that humanity employs with technology. Either it fears, is destroyed, and is overwhelmed by technological progress, or it dictates this progress, drives it forward, and uses it. And then there are two major social constructs that keep the members of society in compliance with the prevailing ideology of life. These are religion and the state.

AI can mimic human thinking abilities like problem-solving and do it faster and more accurately. It's even solved problems thought unsolvable. Google Deepmind's AlphaFold can predict the shape amino acids will fold into, a challenge biologists have wrestled with for the past 50 years. To use the technology to speed up new drug development, Google's parent company Alphabet recently launched Isomorphic Laboratories. While machines outperforming the human brain may seem alarming, businesses are finding when human and machine capabilities are combined, they get the best results.

This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. From Go to StarCraft to Dota, artificial intelligence researchers are creating reinforcement learning systems that can defeat human experts at complicated games. But the bigger challenge of AI is creating RL systems that can team up with humans instead of competing with them. In a new paper, AI researchers at DeepMind present a new technique to improve the capacity of reinforcement learning agents to cooperate with humans at different skill levels. Accepted at the annual NeurIPS conference, the technique is called Fictitious Co-Play (FCP) and it does not require human-generated data to train the RL agents.

Emerging technologies meet both advocates and resistance as users weigh the potential benefits with the potential risks. To successfully implement new technologies, we must start small, in a few simplified forms, fitting a small number of use cases to establish proof of concept before scaling usage. Artificial intelligence is no exception, but with the added challenge of intruding into the cognitive sphere, which has always been the prerogative of humans. Only a small circle of specialists understand how this technology works -- therefore, more education to the broader public is needed as AI becomes more and more integrated into society. I recently connected with Josh Feast, CEO and cofounder of Boston-based AI company Cogito, to discuss the role of AI in the new era of work.

Where does your enterprise stand on the AI adoption curve? Take our AI survey to find out. Emerging technologies meet both advocates and resistance as users weigh the potential benefits with the potential risks. To successfully implement new technologies, we must start small, in a few simplified forms, fitting a small number of use cases to establish proof of concept before scaling usage. Artificial intelligence is no exception, but with the added challenge of intruding into the cognitive sphere, which has always been the prerogative of humans.

Abhinav Agrawal is the CEO of Rocket, an AI-enhanced recruiting agency as well as Hireflow.ai, The pandemic has inspired fear of the incentive to replace employees with machines. As the co-founder of an AI-powered recruiting organization, I expect that AI won't displace recruiting jobs. In fact, I anticipate that AI will become an indispensable tool for recruiters. Ask any recruiter: What's the most tedious aspect of your job?

Explore AI Ignition: Video and podcasts on the future of AI and humans igniting curiosity, interest, and engagement.

When it comes to justifying investment in conversational AI, the primary factor for many companies is cost savings. Thus, from the outset, humans have been pitted against machines in a battle for survival. Natural language understanding and other machine learning techniques have created value by predicting intent and generating responses. However, the shortcomings of those technologies has made it clear that tapping into the knowledge and skills of customer support employees is critical, as currently only humans can deliver the intuition and empathy that customers have come to expect during difficult or exceptional circumstances. Companies are now realizing that for AI to successfully improve customer experience, they must find a delicate balance between technology and human capabilities.