When big models write copy, even scripts and direct films, we see the professional boundaries of mental workers being reconstructed; When intelligent cars enter the road and humanoid robots appear at service windows, we look forward to embodied intelligence better serving people's beautiful lives... While extending human capabilities, artificial intelligence is also profoundly changing the form of employment and entrepreneurship and the structure of the labor market. We not only embrace the infinite possibilities brought by technological progress, but also need to rationally examine challenges and actively adapt to changes. Therefore, this year's Government Work Report proposes to "improve measures to adapt to the development of artificial intelligence technology and promote employment and entrepreneurship". In the era of artificial intelligence, how can we better find employment and start businesses? How to promote the deep integration of artificial intelligence and employment and entrepreneurship? In the fourth Guangming Think Tank Livelihood Forum, we invite experts to jointly explore the new topic of employment and entrepreneurship in the era of artificial intelligence. How does Chen Zhiyin and Chen Heng recognize the impact of artificial intelligence on employment? Bright Think Tank: What profound impact has artificial intelligence had on the job market and what new opportunities has it brought to employment and entrepreneurship? Zhang Chuanchuan: The impact of artificial intelligence on the job market can be generally understood from four levels: labor demand side, supply side, market structure, and market equilibrium results. On the demand side, on the one hand, artificial intelligence can replace some rule-based and repetitive tasks, thereby reducing the labor market demand for certain traditional positions; On the other hand, artificial intelligence will also create new job opportunities through various channels, including directly giving birth to a group of new professions such as AI trainers, algorithm auditors, data annotators, and indirectly driving employment growth by lowering the threshold for entrepreneurship. It should be emphasized that artificial intelligence is often difficult to completely replace a certain profession, and more often manifests as reshaping the task structure within the profession. For example, in many fields, artificial intelligence can undertake tasks such as data processing, information analysis, and text generation, but at the same time requires human participation in decision-making, communication, and collaboration. In other words, more and more professions will take on the form of human-machine collaboration. On the supply side, with the continuous expansion of artificial intelligence applications, workers need to make adjustments in human capital investment to adapt to new job demands. For example, enhancing human-machine collaboration, innovation, and judgment abilities, and strengthening lifelong learning. Meanwhile, due to changes in job demand structure, workers' career transitions and cross industry and cross regional mobility may become more frequent. At the level of market structure, artificial intelligence will also affect the structure and operation mechanism of the labor market. For example, the application of digital platforms and intelligent algorithms in recruitment and job seeking is becoming increasingly widespread, affecting the search and matching process and efficiency in the labor market. At the same time, artificial intelligence has lowered the threshold for digital work, promoted the development of platformization and flexible employment, and made flexible employment forms such as freelance, remote work, and project-based employment more common. Finally, under the combined effect of changes in labor demand structure and supply structure, the equilibrium results of the labor market will also be adjusted, reflected in the overall employment scale, employment structure, wage level, and income distribution pattern. Zhao Guochang: The development of artificial intelligence has also brought new tracks and opportunities for innovation and entrepreneurship. Firstly, the application of artificial intelligence in fields such as content creation, software development, intelligent customer service, and product design has significantly reduced innovation costs and entrepreneurial barriers, enabling individuals or small teams to carry out innovation and entrepreneurship activities with lower investment. At the same time, the artificial intelligence industry chain itself has nurtured a large number of entrepreneurial opportunities around algorithm optimization, data governance, computing power services, and other aspects. More importantly, as artificial intelligence technology continues to advance and is widely applied in production and daily life, its impact will expand from local applications to systematic reshaping of production methods and industrial structures, constantly giving rise to new industrial forms and development spaces, thus opening up a broader track for innovation and entrepreneurship. That is to say, artificial intelligence has given rise to a large number of intelligent application scenarios in fields such as manufacturing, healthcare, education, elderly care, cultural tourism, and agriculture; On the other hand, it also significantly reduces the costs of product prototype development, content production, market analysis, and operational testing. For small and medium-sized teams as well as individual entrepreneurs, this means lower trial and error costs and faster innovation speed. In the era of artificial intelligence, entrepreneurs do not need to be the team with the strongest technology and the richest computing resources. As long as they understand the specific scenarios, user pain points, and can transform technology into practical value, they have the opportunity to stand out. How to lower the threshold for entrepreneurship in the era of artificial intelligence? Bright Think Tank: How to lower the threshold for employment and entrepreneurship in artificial intelligence, improve entrepreneurial services and ecological support, and enable more ordinary people to share the development dividends of the era of artificial intelligence? Zhao Guochang: The key is to transform artificial intelligence from a high threshold technology for a few people into an entrepreneurial tool that more ordinary people can use, afford, and use well. Currently, many small and medium-sized enterprises and individual entrepreneurs are not without ideas, but rather lack access paths, landing capabilities, and controllable cost support conditions. This includes promoting the construction of public computing power platforms, facilitating the open sharing of open source models, industry datasets, and common tools, lowering the threshold for use through methods such as "computing power coupons", and allowing start-up teams to quickly validate products and scenarios without having to invest too much in the early stages. The difficulty of artificial intelligence entrepreneurship is often not just the technology itself, but how to find application scenarios, complete product landing, handle data compliance, and form business models. Artificial intelligence involves issues such as data security, intellectual property, privacy protection, and algorithm governance. If the rules are not clear, entrepreneurs often dare not take action. To this end, it is necessary to better leverage the roles of incubation platforms, industry associations, and professional service organizations to provide technical consultation, scenario docking, compliance counseling, market verification, and other support for entrepreneurs, helping them avoid detours. At the same time, it is necessary to improve relevant rules as soon as possible, clarify boundaries and responsibilities, and reduce institutional uncertainty. Make policy support more adaptable to the entrepreneurial characteristics of small teams, light assets, and rapid iteration in the era of artificial intelligence, and form more inclusive arrangements in financing, taxation, flexible employment security, etc., so that more ordinary people can share the development opportunities brought by artificial intelligence. Zeng Xiangquan: In the era of artificial intelligence, allowing more ordinary people to participate in innovation and entrepreneurship can be approached from three aspects: first, lowering the technological threshold. Drawing on the experience of open source communities in artificial intelligence, we provide a rich set of universal models, API interfaces, and low code platforms, allowing entrepreneurs to develop applications without a strong programming foundation. Build shared algorithm libraries, cloud computing platforms, and low-cost development tools to reduce research and development costs and time costs. The second is to improve entrepreneurial services. Provide full chain services from project incubation, legal and financial guidance to market promotion, establish entrepreneurial mentors and technical consulting to help entrepreneurs avoid detours and land quickly. At the same time, through policy support such as entrepreneurship funds, venture capital, and tax reductions, the difficulty of financing can be reduced. The third is to focus on skill training. By promoting the application of artificial intelligence through online courses, workshops, and community activities, we aim to enhance the digital literacy and innovation capabilities of workers and entrepreneurs, giving more people the confidence to participate in entrepreneurship and strengthening their practical abilities. Zhang Chuanchuan: In addition, we need to strengthen financial support and policy guidance to create an open and inclusive innovation and entrepreneurship ecosystem. Through various channels such as venture capital funds, technology finance products, and government guidance funds, we provide diversified financing support for innovation and entrepreneurship, helping promising entrepreneurial projects grow smoothly. Encourage large technology enterprises, research institutions, and small and medium-sized enterprises to carry out collaborative innovation, promote the transformation and industrial application of artificial intelligence technology achievements. At the same time, we will strengthen data security, intellectual property protection, and algorithm governance to provide a favorable institutional environment for the healthy development of the artificial intelligence industry. How to view the "skill panic" in the era of artificial intelligence? Bright Think Tank: What changes will occur in the core competency requirements and talent development logic of professions in the era of artificial intelligence? With the rapid advancement of artificial intelligence technology, many people have experienced a "skill panic", fearing that their jobs will be replaced by artificial intelligence. How do you view this concern? Zhao Guochang: My opinion is that there should be a sense of urgency, but there is no need to panic. Artificial intelligence will indeed replace some basic, repetitive, and highly standardized job tasks, but this does not mean that most positions will disappear as a whole. More precisely, it is the redistribution of tasks within positions and the redefinition of evaluation criteria for professional abilities. In the era of artificial intelligence, the core competencies of professions are undergoing significant changes. In the past, some positions placed more emphasis on knowledge accumulation, proficiency in procedures, and standard operations; In the future, the ability to define problems, integrate across domains, collaborate with humans, and judge, verify, and take responsibility for results will become increasingly important. Therefore, the logic of talent cultivation should also be adjusted accordingly, shifting from emphasizing knowledge imparting to placing more emphasis on project practice, real-world training, interdisciplinary integration, and continuous learning ability cultivation. It is worth noting that the threshold for "junior jobs" is being raised. In the past, some jobs that were considered highly technical are becoming more standardized and tool based with the assistance of artificial intelligence. That is to say, the previously standardized parts of "advanced work" are rapidly transforming into new "junior work". Therefore, what really needs to be valued is not simply worrying about job disappearance, but adapting to new competency standards as soon as possible, forming judgment, creativity, and trust abilities that artificial intelligence cannot replace. Zhang Chuanchuan: The development of artificial intelligence is reshaping the structure of professional abilities and also putting forward new requirements for the logic of talent cultivation. Overall, in the era of artificial intelligence, workers not only need to have the ability to use AI tools, but also need to possess unique human advantages such as judgment, creativity, communication, and collaboration. Artificial intelligence can largely provide information, analyze and process information, and generate solutions. At the same time, it also has certain limitations, such as incomplete understanding of specific situations and lack of subjectivity in value balancing. Therefore, it is necessary for humans to identify, evaluate, and select the content generated by artificial intelligence. In this sense, a new division of labor is gradually forming between humans and artificial intelligence: artificial intelligence is more responsible for information processing and solution generation, while humans are more responsible for judgment, decision-making, and responsibility. From the perspective of talent cultivation, this means that the education system should not only impart knowledge and cultivate students' calculation and analysis abilities, but also cultivate independent thinking and comprehensive judgment abilities. At the same time, it should strengthen education in values and ethics, guide students to form correct technical views and sense of responsibility. In the stage of rapid technological development, it is understandable that some people may experience a "skill panic". But from historical experience, the key lies in whether the speed of labor skills and social system reconstruction can keep up with the pace of technological progress. For the employment pressure that artificial intelligence may bring in the short term, on the one hand, workers need to actively adjust their ability structure and career development concepts, and continuously improve their digital skills and human-machine collaboration abilities through continuous learning