Creativity involves not only generating new ideas from scratch but also redefining existing concepts and synthesizing previous insights. Among various techniques developed to foster creative thinking, brainstorming is widely used. With recent advancements in Large Language Models (LLMs), tools like ChatGPT have significantly impacted various fields by using prompts to facilitate complex tasks. While current research primarily focuses on generating accurate responses, there is a need to explore how prompt engineering can enhance creativity, particularly in brainstorming. Therefore, this study addresses this gap by proposing a framework called GPS, which employs goals, prompts, and strategies to guide designers to systematically work with an LLM tool for improving the creativity of ideas generated during brainstorming. Additionally, we adapted the Torrance Tests of Creative Thinking (TTCT) for measuring the creativity of the ideas generated by AI. Our framework, tested through a design example and a case study, demonstrates its effectiveness in stimulating creativity and its seamless LLM tool integration into design practices. The results indicate that our framework can benefit brainstorming sessions with LLM tools, enhancing both the creativity and usefulness of generated ideas.

As we assess the risks of AI, we are overlooking a crucial threat. Critics commonly highlight three primary hazards--job disruption, bias, and surveillance/privacy. We hear that AI will cause many people to lose their jobs, from dermatologists to truck drivers to marketers. We hear how AI turns historical correlations into predictions that enforce inequality, so that sentencing algorithms predict more recidivism for Black men than white ones. We hear that apps help authorities watch people, such as Amazon tracking which drivers look away from the road.

The education community has been abuzz with the rise of ChatGPT, an artificial intelligence tool that can write anything with just a simple prompt. Most of the conversation has been centered on the extent to which students will use the chat bot--but ChatGPT could also fundamentally change the nature of teachers' jobs. So far, teachers have used--or considered using--the chat bot to plan lessons, put together rubrics, offer students feedback on assignments, respond to parent emails, and write letters of recommendation, among other tasks. While some educators worry about the implications of automating these parts of teaching, others say that the tool can save them hours of work, freeing up time for student interactions or their personal life. After all, a typical teacher works about 54 hours a week, but just under half of that time is devoted to directly teaching students, according to a nationally representative survey of teachers conducted by the EdWeek Research Center last year. Just under a third of teachers said if they could spend less time on any one task, it would be general administrative work.

IN A POST entitled "Machine Learning: Bane or Blessing for Mankind?", I noted that the renowned theoretical physicist Stephen Hawking along with his colleagues Stuart Russell, Max Tegmark, and Frank Wilczek recommend moving cautiously in the development of artificial intelligence (AI), especially in the area of autonomous weapon systems. Hawking and his colleagues understand, however, that the AI genie has already been released from the bottle and there is no way to get it back in. After noting Hawking's concerns, Ron Neale comments, "Such a warning about the application of AI and its derivative intelligent machines (IMs), especially in the area of military application, might be appropriate. But what if IMs are really just a new branch on the tree of evolution that has led us from the original Protists to where we are today?"

In a bid to help fix the nation's child care crunch, a Tokyo-based start-up is testing a new service combining robots and sensors to monitor kids at nurseries. Global Bridge Holdings, a child care and nursing care venture, is working with academics from Gunma University to develop a system aimed at alleviating the burden of nursery school teachers, many of whom are overworked amid a nationwide staffing shortage. The project features a specially designed bear-shaped robot called Vevo that can greet and identify children and record their body temperatures using a thermograph. During naps, sensors embedded in cots can monitor heart rates and body movements of children to make sure they are breathing. An alarm system will notify teachers if any abnormalities are detected.

An interesting question in contemporary philosophy asks, if a machine can function *precisely* like a human, is there a relevant difference between the machine and the human? The answer seems to be, "no." So if it were possible to have an AI program function *precisely* like a school teacher, I see no problem in using such a machine. The problem is in the making: (1) what does a school teacher do? (2) how can a machine do it? It's easy to see phone operators replaced by machines.

The world's first social robot went on show at the South by Southwest (SXSW) function in Austin on Saturday. JIBO has been specifically designed to serve in the home, offering various useful functions which accommodate to a domestic setting, including home security, storytelling and entertainment. Commenting on the robot's qualities, software developer Jonathan Ross said that "JIBO is a social robot for the home he can recognise you by your face by your voice" adding that "he can understand what you are saying and it can talk back to you." He went on to explain that humans "are hard wired to be responsive to social interactions. So by having a piece of hardware that actually acts like a person and can acknowledge you and can have a social presence, we can tap into that."