Human Artificial Intelligence Ai Interaction Latest Advances And

Correia, A.; Schneider, D.; Fonseca, B.; Kärkkäinen, T. Human–Artificial Intelligence (AI) Interaction: Latest Advances and Prospects. Appl. Sci. 2025, 15, 12218. https://doi.org/10.3390/app152212218

Correia A, Schneider D, Fonseca B, Kärkkäinen T. Human–Artificial Intelligence (AI) Interaction: Latest Advances and Prospects. Applied Sciences. 2025; 15(22):12218. https://doi.org/10.3390/app152212218 Correia, António, Daniel Schneider, Benjamim Fonseca, and Tommi Kärkkäinen.

2025. "Human–Artificial Intelligence (AI) Interaction: Latest Advances and Prospects" Applied Sciences 15, no. 22: 12218. https://doi.org/10.3390/app152212218 Correia, A., Schneider, D., Fonseca, B., & Kärkkäinen, T. (2025).

Human–Artificial Intelligence (AI) Interaction: Latest Advances and Prospects. Applied Sciences, 15(22), 12218. https://doi.org/10.3390/app152212218 Your research is the real superpower - learn how we maximise its impact through our leading community journals Artificial Intelligence (AI) has steadily transformed various facets of our daily lives, from automating routine tasks to providing personalized recommendations. As AI technology continues to advance, one of its most profound impacts is expected to be on Human-Computer Interaction (HCI).

This article explores how AI is poised to elevate HCI to unprecedented levels, focusing on the advancements, potential applications, and implications of these technologies. To understand the transformative potential of AI in HCI, it's crucial to look at how human-computer interactions have evolved. Initially, HCI was dominated by command-line interfaces, where users had to memorize and input precise commands. The advent of graphical user interfaces (GUIs) in the 1980s, with icons, windows, and menus, revolutionized how people interacted with computers, making them more accessible and intuitive. The next significant leap came with touch interfaces, which allowed users to interact with devices through gestures and taps. Today, we are on the cusp of another revolutionary change, driven by AI, which promises to make interactions more natural, intuitive, and personalized.

One of the most promising areas of AI in HCI is Natural Language Processing (NLP). NLP enables computers to understand and respond to human language in a way that feels natural. Chatbots and virtual assistants like Siri, Alexa, and Google Assistant are early examples of NLP applications that have become commonplace. However, AI's role in NLP is rapidly advancing, leading to more sophisticated and contextually aware interactions. Each Time AI Gets Smarter, We Change the Definition of Intelligence As AI systems exceed one benchmark after another, our standards for “humanlike intelligence” keep evolving

By Deni Ellis Béchard edited by Clara Moskowitz “When will AI achieve humanlike intelligence?” I recently asked a friend. “It already has,” he replied, suggesting that if you were to travel back in time to 1995 and evaluate our current versions of artificial intelligence from that vantage, most people would consider the technology’s... The goalposts for humanlike intelligence, he said, keep shifting each time AI improves. Intelligence has never been easy to define. For decades, we’ve debated what makes up analytical, creative and emotional intelligence in people, weighing the value of instruction-following against autonomy.

We’ve done the same with machines, and my friend is right: the target we’ve set for AI intelligence has continually moved. Work in the future will be a partnership between people, agents, and robots—all powered by artificial intelligence. While much of the current public debate revolves around whether AI will lead to sweeping job losses, our focus is on how it will change the very building blocks of work—the skills that underpin... Our research suggests that although people may be shifted out of some work activities, many of their skills will remain essential. They will also be central in guiding and collaborating with AI, a change that is already redefining many roles across the economy. In this research, we use “agents” and “robots” as broad, practical terms to describe all machines that can automate nonphysical and physical work, respectively.

Many different technologies perform these functions, some based on AI and others not, with the boundaries between them fluid and changing. Using the terms in this expansive way lets us analyze how automation reshapes work overall.1Our analysis considers a broader range of automation technologies than the narrow definition of agents commonly used in the AI... For more on how we define the term, see the Glossary. This report builds on McKinsey’s long-running research on automation and the future of work. Earlier studies examined individual activities, while this analysis also looks at how AI will transform entire workflows and what this means for skills. New forms of collaboration are emerging, creating skill partnerships between people and AI that raise demand for complementary human capabilities.

Although the analysis focuses on the United States, many of the patterns it reveals—and their implications for employers, workers, and leaders—apply broadly to other advanced economies. We find that currently demonstrated technologies could, in theory, automate activities accounting for about 57 percent of US work hours today.2Our analysis focuses exclusively on paid productive hours in the US workforce, encompassing full-time... We assess only the share of time awake that is spent on work-related activities, totaling roughly 45 percent of waking hours. Our analysis excludes time spent on unpaid tasks and leisure, but agents and robots could be used in related activities to support productivity and personal well-being. This estimate reflects the technical potential for change in what people do, not a forecast of job losses. As these technologies take on more complex sequences of tasks, people will remain vital to make them work effectively and do what machines cannot.

Our assessment reflects today’s capabilities, which will continue to evolve, and adoption may take decades. Human-computer interaction focuses on how people interact with computers and developing ergonomic designs of computers to better fit the needs of humans. Although the definition shifts as its technical progress,[1] artificial intelligence (AI) is distinguished from general computers for its ability to complete tasks that are usually executed with human intelligence. Its intelligence reads especially human-like as it involves navigating uncertainty, active learning, and processing information just as humans see and hear.[2][3] Unlike the traditionally hierarchical human-computer interaction, where a human directed a machine, human-AI... Human-AI interaction has a strong influence on the world as AI changes how people behave and make sense of the world[5] as AI is widely used today for building algorithms to show individualized advertisements... AI has been perceived with various expectations, attributions, and often misconceptions.[7] Most fundamentally, humans have a mental model of understanding AI's reasoning and motivation for its decision recommendations, and building a holistic and precise...

Human-AI collaboration occurs when the human and AI supervise the task on the same level and extent to achieve the same goal.[11] Some collaboration occurs in the form of augmenting human capability. AI may help human ability in analysis and decision-making through providing and weighing a volume of information,[12] and learning to defer to the human decision when it recognizes its unreliability.[13] It is especially beneficial... Some findings show signs of human-AI augmentation,[14] or human–AI symbiosis,[15] in which AI enhances human ability in a way that co-working on a task with AI produces better outcomes than a human working alone.[14]...

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