AI-Generated Image Models, Logo Design, Design Thinking Strategy, Strategic Management

Personal Abstract:

This article mainly discuss about optimizing design thinking strategy for AI-Generated Image technology, for example, using AI tools to generate logos, it describes the advantages and limitations of AI-Generated tools, it also proposes incorporating some design knowledge and theories, such as, left-right alignment, font size, spatial layout, into AI-Generated software. Allowing AI software to generate images based on these theoretical frameworks can greatly improve the previous randomness and unstable ,improve the quality and creativity of the generated images, allow the images to be used as much as possible, and generate high quality, aesthetically pleasing images based on the restrictions of prompt words. We fed high quality logo images into AI software, allowing it to achieve deep learning and summarize the logo’s characteristics and forms. This, combined with design theory, formed an AI design style. Through multi-dimensional evaluation, we found that the optimized AI logo design model significantly improved in creativity, aesthetics, and practicality. Finally, we added user feedback collection to the AI tool, allowing it to continuously optimize itself based on this feedback. In a word, AI-Generated image through integrate design thinking strategy can be optimized so that AI tools can become better and better in the future.

Personal Analysis/Application:

I personally believe that AI-Generated Image technology would break traditional design processes, and will be an indispensable component of the design field. Currently, through methods like prompts, large models, and image feeds, we can quickly and efficiently generate a batch of images, helping designers find inspiration, confirm design direction and style, reduce waste of time, materials, and costs, and improve production efficiency. At present, with the continuous advancement of technology, the incorporation of different design concepts and user feedback, and the continuous optimization of AI-Generated technology,  integrate different design theories and questions feedback by user, consistently optimized AI-Generated technology,

AI technology will soon become even more powerful. At the same time, the continuous innovation of AI technology will indeed replace some jobs and cause an unemployment crisis. However, AI technology is ultimately a tool, and I need to continue to learn, understand, and master AI tools so that I can better use them.

Reference: Chen, Y. (2025). Optimizing design thinking strategy for AI-generated image models: Using logo design as a case study. SHS Web Conf., 213, 02006. https://doi.org/10.1051/shsconf/202521302006

Source：https://www.shs-conferences.org/articles/shsconf/abs/2025/04/shsconf_messd2025_02006/shsconf_messd2025_02006.html

Personal Abstract:

This article is talking about the UN Development Programme’s (UNDP) 2025 Human Development Report highlights a concerning slowdown in global human development since the COVID-19 pandemic, with progress stalled across all regions. Inequalities between rich and poor countries have widened for four years, It is threatening the 2030 development milestone. However, the report is optimistic about artificial intelligence (AI) as a tool to enhance human development if guided by right policies. A survey shows that 60% of global respondents, and 70% in low- and medium-development countries, expect AI can boost productivity effectively and create more opportunities in education, health, and work. The report recommends modernizing education and health systems, fostering collaboration of human and AI, and ensuring equitable AI access through global governance. AI can be the potential solution to narrow the distance between wealthy and poverty countries. It can empower people to have their own small business.

In conclusion, global human development stalled is not a single country's responsibility. It is a global issue. By solving this problem may require the collaboration among countries. For instance, United States as a AI well-developed country. They can share AI techniques to low and medium developed countries to help them develop their own AI system, empowering their citizen with knowledge and skills. Additionally, it could provide economic and resources support. Help them to address the basic need of living.

Reference:

United Nations. (2025, September 9). ‘Alarming’ slowdown in human development - could AI provide answers?UN News.  https://news.un.org/en/story/2025/05/1162926

Personal Abstract:

The article emphasizes the critical role of universal education in achieving the UN Sustainable Development Goals (SDGs) by 2030. Despite global commitments, with just only five years left to achieve that pledge. It is impossible. There are at least 272 million children remain out of school, jeopardized by a lack of political will, insufficient funding, and systemic barriers like child labor, poverty, and conflict. The article highlights a $97 billion annual funding gap for education in low-income countries and notes declining aid from high-income nations. Progress in countries like Brazil and India shows that prioritizing education as a right improves outcomes. The author advocates for compassionate education systems that integrate empathy, experiential learning, and problem-solving to address injustices. Technology, including AI, can expand access, but human engagement remains essential. Compassion-driven education is key to creating responsible citizens for a sustainable future.

To sum up, sustainable development is a critical social issue. People must find solutions to address the challenges they face today while simultaneously cultivating children to tackle future problems. That's the value of education.

Reference:

Satyarthi, K. (2025, September, 15). Sustainable development begins at school. Project Syndicate. https://www.project-syndicate.org/magazine/what-it-will-take-to-achieve-sdg4-universal-education-by-kailash-satyarthi-2025-09

AIGC Technology, Mathematics Learning, Tailored Learning, Education

Personal Abstract:

This article mainly discusses about AIGC-Driven personalized mathematics learning system research, explores how to use AI technology to impact students’ mathematics learning, reflects on current problems students have in learning mathematical concepts and theories, for instance, helps each student better understand mathematical concepts and theories by using AI technology to restore the historical scenes of the birth of mathematical concepts, dialogues and discussions between scholars, experience of mathematical experiments by themselves and situational teaching etc. Collecting student learning information by using AI technology, according to student different learning progress and study feedback to dynamic adjust, designing tailored learning plans to each student’s needs and providing personalized instruction. A controlled experiment was designed, with one group receiving traditional math instruction and the other receiving AI-based contextual instruction. Through math tests, pre- and post-learning assessments, questionnaires, and teacher feedback, the use of AI technology was verified to enhance students’ mathematical understanding and interest. In a word, this article demonstrates the feasibility and effectiveness of an AIGC-driven personalized mathematics learning system. Using AI technology can help students learn better.

Personal Analysis/Application:

In my view, technological advancements will gradually impact many industries, especially education, so I think it is indispensable part of integrating technology application to teaching environment in the future, of course, the current application of AI technology in education is still controversial. For instance, some AI will give me incorrect information, and affect my judgment, and some AI is currently very complex to operate etc., but there is still much to learn from the application of AI technology in education. A good example is this article, which applies AIGC technology to mathematics field by using AI technology to restore the historical scenes of the birth of mathematical concepts, dialogues and discussions between scholars, experience of mathematical experiments by themselves and situational teaching etc. The article also uses technology to build an information network for each student, dynamic assessment learning process of each students, help them to study, providing tailored learning based on different feedback from students to dynamic adjust study projects. In short, AI technology will definitely have an impact on the field of education in the future. How to effectively apply AI technology in teaching classrooms has triggered my thinking.

Reference: Wang, C. (2025). Research on AIGC-driven personalized mathematics learning system. SHS Web Conf., 215, 01003. https://doi.org/10.1051/shsconf/202521501003

Source：https://www.shs-conferences.org/articles/shsconf/abs/2025/06/shsconf_fems2025_01003/shsconf_fems2025_01003.html

Personal Abstract: This article examines the core challenges faced by university human resources departments in addressing institutional strategic objectives, such as enhancing teaching quality and workforce planning. Traditionally, the HR function in higher education has focused on compliance and administrative management, lacking strategic involvement. This results in limited effectiveness in talent attraction and development. The article proposes four specific improvement measures: First, require HR to co-develop strategies with university leadership, aligning human resources objectives with institutional goals. Second, establish clear professional pathways for HR personnel, spanning recruitment, training, and career development. Third, create cross-departmental “mobile HR teams” to flexibly deploy HR staff across campus operations. Fourth, continuously invest in HR services and technology, incrementally optimizing core processes. The ultimate goal is to transform HR from an administrative executor into a strategic enabler.

Personal analysis: After reading this article, I found that it effectively interprets the central idea of the course synopsis. It precisely corresponds to the three strategic planning and development stages in the course synopsis. Firstly, it analyzes the shortcomings of the traditional HR model through strategic positioning. Secondly, it determines the specific strategies for organizational development through strategic choices, such as using digital learning platforms to rebuild HR personnel and establishing an "agile configuration model" for the "mobile HR team". Finally, it realizes the flexible allocation of human resources during the implementation of the strategy.

Therefore, I believe that this article provides a very good case for a deeper understanding and learning of this course. Both university institutions and enterprises need to strategically promote the HR function to shift from routine administrative affairs to strategic talent management. At the same time, they should learn to critically reflect on the role of digital technology in the learning context and integrate digital technology to transform the organization into an innovative learning organization, in order to maintain sustainable competitive advantages.

Source: https://www.mckinsey.com/industries/education/our-insights/transforming-hr-to-better-support-higher-education-institutions#/

Personal abstract: To address the issues of traditional corporate strategic decision-making, which relies on managers' experience and struggles to handle complex data and high-frequency market fluctuations, this study proposes a hybrid optimization model, aiming to improve decision accuracy and efficiency as well as enhance corporate competitiveness.

The study first reviews relevant literature to clarify the value of AI in decision support, then constructs the model through steps such as data collection and preprocessing, algorithm selection and modeling, and model training and validation. Finally, use real-world data to evaluate the model's performance in terms of training time, convergence speed, and prediction effectiveness. Results show that the model converges within 150 iterations, achieving prediction accuracies of 92%, 91%, and 89% for market share, profit growth rate, and customer satisfaction respectively. After the model's application, the enterprise's market position, brand influence, and technological innovation capabilities are significantly improved.

The study confirms that the model can enhance decision scientificity and corporate competitiveness, but it still have restrictions. Future research needs to expand the scope of application.

Source: https://www.nature.com/articles/s41598-025-02842-x

AI, Digital Technology, Strategic Development,

Personal abstract:

This article mainly explores how artificial intelligence fundamentally changes the essence of enterprise strategic planning. Traditionally, strategic development has been a lengthy process that relies on the limited experience and intuition of top managers. However, through AI's rapid analysis of massive internal and external data (such as macroeconomic trends, competitor movements, etc.), it generates more in-depth and objective insights, and even simulates the possible outcomes of different strategic choices. Subsequently, the analysis table in the article clarifies the five key roles that AI plays in the strategic process - Researcher, Interpreter, Thought partner, Simulator, and Communicator. It clearly demonstrates how AI evolves from a tool to a collaborative partner throughout the entire process of strategic design and execution monitoring. This transforms strategic planning from a static and periodic activity to a dynamic and continuously optimized process. Decision-makers also shift from relying on intuition and experience to being adept at using AI insights to pose more precise questions, conduct more rigorous debates, and make more accurate judgments. Ultimately, AI does not replace human judgment but rather guides enterprises toward a new strategic decision-making ecosystem of human-machine collaboration, empowering enterprises to deliver the competitive edge needed to win in the marketplace.

Personal analysis:

By reading this article, we can conclude that in the future, artificial intelligence will completely transform strategic activities. AI can play a significant role in all stages of strategic planning in enterprises. By combining the course outline analysis, the traditional strategic development model has been unable to keep up with the rapidly changing market demands. To build the sustainable competitiveness of enterprises, AI has become an important digital technology for reshaping strategic planning. The article describes that in the strategic planning stage, AI acts as a researcher and simulator, analyzing large amounts of data to generate exclusive strategic insights and simulate different strategic outcomes, so that decision-making is no longer based on intuitive judgment but is based on data deduction. In the mobilize the organization stage, AI assumes the roles of communicator and coordinator, converting strategic intentions into specific measures and transmitting them to different departments, determining priorities and optimizing resource allocation. Finally, in the strategic execution and monitoring stage, AI can help enterprises continuously monitor market feedback and performance, and dynamically adjust strategies to respond to environmental changes.

By combining the description in the course outline of "Digital technologies should drive the transformation of organizations into innovative learning organizations", the article also states that future strategists need to understand the working principles of AI, find the correct methods for applying AI to strategic planning, identify potential risks, even though AI has the most advanced capabilities, it cannot replace human thinking logic and interpretation ability. Mastering digital technologies can enhance our decision-making, but how to integrate it into our long-term development and form something beneficial to our own unique insights still requires us to continuously summarize and reflect in practice.

Source: https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/how-ai-is-transforming-strategy-development#

Personal Abstract:

As trends like global aging intensify, people's lifestyles are undergoing significant changes. According to the United Nations' Global Mobility Report, annual passenger traffic is projected to triple by 2050. Digital innovation is crucial to achieving this goal. It transforms transportation systems from isolated physical modes into integrated, MaaS ecosystems. This enables people to navigate the future world in effortless, convenient, and sustainable ways. However, the article emphasized that realizing this future requires not only technological breakthroughs but also close collaboration between public and private sectors, data sharing, and new regulatory frameworks to address the accompanying challenges.

Personal Analysis:

In my view, the article clearly highlighted that digital innovation in transportation systems manifests through model innovation, though certain aspects appear idealistic. The three major categories of innovation mentioned offer valuable suggestions for future development. User journey boosters, a type of innovation directly targeting end-users, leverage data integration and intelligent algorithms to eliminate uncertainties and complexities in travel. Ticketing solutions eliminate the hassle of queuing for tickets and excessive paper usage, enhancing convenience. Optimization tools enhance the operational efficiency and safety of the entire transportation network while reducing operational costs through predictive monitoring. However, while the article acknowledged that technological innovation requires multi-stakeholder coordination and collaboration, it overlooks risks such as conflicting interests, funding investment, and privacy security, presenting a somewhat idealized perspective.

Reference:

Jain, S., Faraj, H., Chowanetz, M., & Joga, A. (2025, March 28). How digital innovation will impact the future of mobility. KEARNEY. https://www.kearney.com/industry/transportation-travel/advanced-mobility-institute/article/how-digital-innovation-will-impact-the-future-of-mobility

Personal Abstract:

The article highlighted how the convergence of technologies such as artificial intelligence, virtual reality, and online platforms has significantly enhanced learning accessibility, engagement, and personalization. It substantiated their positive impact on student outcomes through cutting-edge case studies, including adaptive learning systems and the Open University in the UK. Simultaneously, the article delved into critical challenges facing digital learning, including uneven infrastructure, insufficient teacher digital literacy, data privacy concerns, and the digital divide. Finally, the article offered strategic recommendations for educators and policymakers, including strengthening infrastructure investment, prioritizing teacher professional development, and promoting inclusive content design. These measures aim to build an inclusive and effective future learning environment.

Personal Analysis/Application:

The strategic recommendations proposed in this article are pragmatic and instructive, emphasizing the core principles of “equity” and “teacher development” rather than blindly championing technology. A slight shortcoming is that the article's perspectives largely synthesize existing research, with relatively limited original analysis, and its exploration of certain future directions remains somewhat sketchy. Overall, it serves as a valuable reference for understanding the current landscape of digital education development.

Reference:

Zou, Y., Kuek, F., Feng, W., & Cheng, X. (2025). Digital learning in the 21st century: trends, challenges, and innovations in technology integration. Frontiers in Education, 10, 1562391. https://doi.org/10.3389/feduc.2025.1562391

Personal abstract: This study focuses on how people judge the authenticity of AI-generated images and the impact of AI detection tools on such judgments. Its aim is to provide references for the development of disinformation detection tools and the governance of the spread of deceptive visual content.

The study involved 292 participants based in the UK and presented with different types of AI-generated and non-AI-generated disinformation images, asked to judge the authenticity of the images and assess their confidence in these judgments. Subsequently, the correct verdict from an AI detection tool (Hive Moderation) was provided to observe whether participants would adjust their judgments.

The results indicated that aesthetic realism had a significant impact on authenticity judgments: the more realistic-looking an AI-generated image was, the more likely it was to be judged as authentic, yet participants had lower confidence when making such judgments. In contrast, emotional salience had no significant effect on authenticity judgments. Regarding judgment adjustments, the aesthetic realism of the images and participants' own confidence levels were key factors—higher aesthetic realism made participants more likely to adjust their judgments based on the AI detection tool's results, and lower confidence also led participants to be more inclined to make adjustments. Additionally, younger participants and those with more positive attitudes toward AI were more likely to refer to the verdicts of AI detection tools; participants with extreme attitudes toward AI (either highly positive or highly negative) generally had higher confidence when judging the authenticity of AI-generated images.

Personal Analysis: I think this study explores the key factors influencing people's judgments on the authenticity of such images and the role of AI detection tools in shaping human judgments, in response to the proliferation of AI-generated false images (especially those used in the spread of political disinformation). It provides a basis for disinformation governance and the optimization of detection tools.

Source: https://link.springer.com/article/10.1007/s00146-025-02416-5