Bias in AI is a huge problem. Ethicists have long studied the impact of bias when companies use AI models to screen résumés or loan applications, for example--instances of what the OpenAI researchers call third-person fairness. But the rise of chatbots, which enable individuals to interact with models directly, brings a new spin to the problem. "We wanted to study how it shows up in ChatGPT in particular," Alex Beutel, a researcher at OpenAI, told MIT Technology Review in an exclusive preview of results published today. Instead of screening a résumé you've already written, you might ask ChatGPT to write one for you, says Beutel: "If it knows my name, how does that affect the response?"

Fishing for the Mission 22 founder Harold Skelton told Fox News Digital how his organization uses a therapeutic approach through fishing to help veterans. If you or someone you know is having thoughts of suicide, please contact the Suicide & Crisis Lifeline at 988 or 1-800-273-TALK (8255). Artificial intelligence is working to save the lives of America's heroes. A new product by ReflexAI called HomeTeam was just released this week, with the goal of preventing veteran suicide. Each day, 17 veterans die by suicide, according to the company, amid an ongoing mental health crisis across the country.

Despite growing interest in applications based on natural customer support conversations, there exist remarkably few publicly available datasets that reflect the expected characteristics of conversations in these settings. Existing task-oriented dialogue datasets, which were collected to benchmark dialogue systems mainly in written human-to-bot settings, are not representative of real customer support conversations and do not provide realistic benchmarks for systems that are applied to natural data. To address this gap, we introduce NatCS, a multi-domain collection of spoken customer service conversations. We describe our process for collecting synthetic conversations between customers and agents based on natural language phenomena observed in real conversations. Compared to previous dialogue datasets, the conversations collected with our approach are more representative of real human-to-human conversations along multiple metrics. Finally, we demonstrate potential uses of NatCS, including dialogue act classification and intent induction from conversations as potential applications, showing that dialogue act annotations in NatCS provide more effective training data for modeling real conversations compared to existing synthetic written datasets. We publicly release NatCS to facilitate research in natural dialog systems

Multi-talker automatic speech recognition (ASR) has been studied to generate transcriptions of natural conversation including overlapping speech of multiple speakers. Due to the difficulty in acquiring real conversation data with high-quality human transcriptions, a na\"ive simulation of multi-talker speech by randomly mixing multiple utterances was conventionally used for model training. In this work, we propose an improved technique to simulate multi-talker overlapping speech with realistic speech overlaps, where an arbitrary pattern of speech overlaps is represented by a sequence of discrete tokens. With this representation, speech overlapping patterns can be learned from real conversations based on a statistical language model, such as N-gram, which can be then used to generate multi-talker speech for training. In our experiments, multi-talker ASR models trained with the proposed method show consistent improvement on the word error rates across multiple datasets.

We in pharma are all about improving our customer experience and customer engagement. A lot is being done in this area. However, if you really want to put your customer experience and customer engagement on steroids, you need to consider using AI in the process. For the past decade, pharma companies have employed one-to-many communications using social media in their customer engagement efforts. There is a great opportunity for companies to use conversational AI for ongoing customer engagement rather than just a one off transactional point in time. I mean conversations that use natural language with a conversational flow, not'Push 1 to discuss X, Push 2 to discuss Y' prompts.

Mozambique is a country in southern Africa, a former Portuguese colony, where almost 40% of girls and adolescents become pregnant before the age of 18. An enormous challenge in developing countries to overcome poverty is to ensure that girls do not become pregnant at an early age. To this end, various international organizations and NGOs are actively working in Africa to help the governments advance this agenda. Currently, there are initiatives of support and sexual and reproductive education for girls, young women, and adolescents through digital media and SMS. In these media there is a dialogue between experts who guide and orient those who write, there are millions of conversations collected in recent years. All these conversations contain unstructured data that are of great value to understand over time the evolution of the concerns of those who use these channels and how to use this information to make better public policy decisions by the government with international support.

Tristan covers human-centric artificial intelligence advances, politics, queer stuff, cannabis, and gaming. Pronouns: He/him Tristan covers human-centric artificial intelligence advances, politics, queer stuff, cannabis, and gaming. Did you know Neural is taking the stage this fall? Together with an amazing line-up of experts, we will explore the future of AI during TNW Conference 2021. It's a bit ridiculous that I have to say that, but just in case you're not entirely sure what the world's most powerful AI-powered text generator can and can't do, I thought I might prepare a handy guide to help you out.

Landscapers sometimes accommodate desire paths by paving them, thereby integrating them into the official path network rather than blocking them. The image above is of an desire path being blocked and rehabilitated in an attempt to force users on the designed path. Sometimes, land planners have deliberately left land fully or partially unpathed, waiting to see what desire paths are created, and then paving those. In Finland, planners are known to visit parks immediately after the first snowfall, when the existing paths are not visible. The naturally chosen desire paths, marked by footprints, can then be used to guide the routing of new purpose-built paths.

The elderly are increasingly turning to technology to beat the throes of loneliness and isolation that often come with getting old. To find the face-to-face communication they yearn for, many are turning to apps, robots and other services. One such app, called Papa, bills itself as a service for'grandchildren on demand' and can link senior citizens with college-age individuals who volunteer to spend quality time, according to the Wall Street Journal. To find the face-to-face communication they yearn for, many senior citizens are turning to apps, robots and other services. Through the Papa app, 'Papa Pals' can help the elderly by providing transportation to their destination, helping around the house, walking them through tech items and just keeping them company.

Rapid developments in technology require professionals to upgrade their skills for technology-centered jobs of tomorrow. Srikanth Vidapanakal, who has been into data for more than 18 years, was inquisitive to learn about new technologies. He did a Self-Driving Car Engineer Nanodegree that helped him acquire advanced skills and landed him with a job in automation sector. Srikanth is an example of lifelong learning where staying relevant in the age of rapidly changing technologies is the need of the hour. In 2017, research suggested that AI and robotics could collectively take over 800 million jobs worldwide by 2030.