Many people suffer from mental health problems but not everyone seeks professional help or has access to mental health care. AI chatbots have increasingly become a go-to for individuals who either have mental disorders or simply want someone to talk to. This paper presents a study on participants who have previously used chatbots and a scenario-based testing of large language model (LLM) chatbots. Our findings indicate that AI chatbots were primarily utilized as a "Five minute therapist" or as a non-judgmental companion. Participants appreciated the anonymity and lack of judgment from chatbots. However, there were concerns about privacy and the security of sensitive information. The scenario-based testing of LLM chatbots highlighted additional issues. Some chatbots were consistently reassuring, used emojis and names to add a personal touch, and were quick to suggest seeking professional help. However, there were limitations such as inconsistent tone, occasional inappropriate responses (e.g., casual or romantic), and a lack of crisis sensitivity, particularly in recognizing red flag language and escalating responses appropriately. These findings can inform both the technology and mental health care industries on how to better utilize AI chatbots to support individuals during challenging emotional periods.

In the early stages of the design process, designers explore opportunities by discovering unmet needs and developing innovative concepts as potential solutions. From a human-centered design perspective, designers must develop empathy with people to truly understand their needs. However, developing empathy is a complex and subjective process that relies heavily on the designer's empathic capability. Therefore, the development of empathic understanding is intuitive, and the discovery of underlying needs is often serendipitous. This paper aims to provide insights from artificial intelligence research to indicate the future direction of AI-driven human-centered design, taking into account the essential role of empathy. Specifically, we conduct an interdisciplinary investigation of research areas such as data-driven user studies, empathic understanding development, and artificial empathy. Based on this foundation, we discuss the role that artificial empathy can play in human-centered design and propose an artificial empathy framework for human-centered design. Building on the mechanisms behind empathy and insights from empathic design research, the framework aims to break down the rather complex and subjective concept of empathy into components and modules that can potentially be modeled computationally. Furthermore, we discuss the expected benefits of developing such systems and identify current research gaps to encourage future research efforts.

They threatened the system with death if it failed to comply with their instructions. It ended up conceding, which is shocking. Only humans should experience the fear of death since they have finite lifespans. But we forget that the training data set used for ChatGPT involves humans. This explains why chatbot seems to have adopted this fear too.

In a proliferated, multi-channel world, every brand needs to win the heart and mind of the consumer to acquire and retain them. They need to set up a foundation of empathy and connectedness. Artificial intelligence combined with a human-centric approach to marketing might seem like a contrarian model. But the truth is that machine learning, AI and automation are vital for brands today to transform data into empathetic, customer-centric experiences. For marketers, AI-based solutions serve as a scalable and customizable tool capable of understanding the motive behind consumer interactions.

Artificial intelligence combined with a human-centric approach to marketing might seem like a contrarian model. But the truth is that machine learning, AI and automation are vital for brands today to transform data into empathetic, customer-centric experiences. For marketers, AI-based solutions serve as a scalable and customizable tool capable of understanding the motive behind consumer interactions. This is the power of artificial empathy: When brands target individual consumer needs and connect with them at a deeper level than mere transactional exchanges. When it comes to empathetic machines, Hollywood may have made us think of the likes of Wall-E: robots with emotions. But artificial empathy is fundamentally about giving technology the ability to discover and respond to human emotions.

A blank stare and dark face, just like in the movie Red Heat: Russians are global leaders in hiding their emotions. But a new generation of tech entrepreneurs is trying to get under the tough guys' skin and also inside their brains. Among pioneers of emotional intelligent tech in Russia are Moscow-based startups Neurodata Lab and NTechLab. Rosbank, a subsidiary of Paris-based Société Générale financial group, is now testing an emotion recognition technology developed by Neurodata Lab at its call centers. The solution calculates a "Customer Satisfaction Index" in real time by analyzing both voice and speech.

Siri, Alexa, or Google Assistant can set a timer, play a song, or check the weather with ease, but for a real conversation you may as well try talking to the toaster. Speaking as naturally as a person requires common-sense understanding of the world, knowledge of facts and current events, and the ability to read another person's feelings and character. It's no wonder machines aren't all that talkative. A chatbot developed by artificial intelligence researchers at Facebook shows that combining a huge amount of training data with a little artificial empathy, personality, and general knowledge can go some way toward fostering the illusion of good chitchat. The new chatbot, dubbed Blender, combines and builds on recent advances in AI and language from Facebook and others.

What do you think when someone asks you about empathy? Do you struggle to find its meaning or does it come to you naturally? In the age of artificial intelligence, do our AI systems need empathy? If so, what are some use cases where empathy can be most helpful in AI Systems? When we read a book out loud to our children, they can hear the emotions we imbue into the passages.

Human advancement has been driven by the improvement of tools, machines and innovation that enlarge our regular abilities. However, our emotional mind – the part that controls our empathy has had little assistance from innovation to-date. Artificial Intelligence (AI) has the ability to change that. Structuring human-driven AI interactions, improved to create confided relationships between AI and people, displays the biggest opportunity for human and societal progression in the cutting-edge period. Augmented reality is just convincing if that the truth is as close to the real reality that you experience as could be expected under the circumstances.

Customer service calls can be ... infuriating. Part of the reason is that humans generally aren't great at reading subtle emotional cues, especially if we only have voice to go by. At the same time, we often inadvertently broadcast unintended emotional signals, easily leading to miscommunication and discomfort over the phone. But an MIT spinoff called Cogito is using voice analytics to help customer service reps better understand how customers are feeling. The technology behind Cogito's enterprise product, which can predict a customer's emotional state by analyzing tone and voice patterns, has also been used to identify signs of PTSD and depression in veterans.