CODE 113763 ACADEMIC YEAR 2024/2025 CREDITS 1 cfu anno 1 DESIGN NAVALE E NAUTICO 9008 (LM-12) - LA SPEZIA 1 cfu anno 2 DESIGN NAVALE E NAUTICO 9008 (LM-12) - LA SPEZIA SCIENTIFIC DISCIPLINARY SECTOR ICAR/13 LANGUAGE Italian TEACHING LOCATION LA SPEZIA SEMESTER 1° Semester MODULES Questo insegnamento è un modulo di: TOOLS AND STRATEGIC DISCIPLINES FOR DESIGN TEACHING MATERIALS AULAWEB AIMS AND CONTENT LEARNING OUTCOMES The teaching, focused on the integration of generative artificial intelligence in the field of design, aims to reveal the capabilities and applications of generative AI. Through hands-on laboratory exercises, students will learn how this technology is able to improve the efficiency of design processes, assist in creative decisions and be used effectively at various stages of the design cycle. AIMS AND LEARNING OUTCOMES Become familiar with the main generative AI tools (text-to-text, text-to-image, text-to-video). Learn to effectively and responsibly integrate generative tools into the design process. Reflect critically on the creative, technical, and ethical use of generative AI in design. Experiment with AI tools to generate visual and textual content supporting design ideation. PREREQUISITES Ability to analyse and solve complex design-related problems. Basic knowledge of programming concepts and ability to use design software Familiarity with digital tools and online collaboration platforms. Basic knowledge of calculus and statistics. Ability to apply quantitative methods for analysing and solving design problems. Ability to critically evaluate the ethical and practical implications of emerging technologies in design. TEACHING METHODS The teaching activity will be provided in person through lectures and exercises. SYLLABUS/CONTENT Introduction to generative models: definition and working principles Overview of text-to-text (e.g., ChatGPT), text-to-image (e.g., DALL·E, Midjourney), and text-to-video (e.g., Runway, Pika) tools Use cases of generative AI tools in design workflows Prompt experimentation and generation of visual/textual content Critical reflection on risks, bias, and ethical aspects of generative AI Case study discussions and design best practices RECOMMENDED READING/BIBLIOGRAPHY To follow the module, the material provided by the teacher will be sufficient. TEACHERS AND EXAM BOARD ANDREA VIAN Ricevimento: To be agreed by email: andrea.vian@unige.it Exam Board FILIPPO BERTANI (President) MARIA MOROZZO DELLA ROCCA E DI BIANZE' ANNALISA BARLA (President Substitute) ANDREA VIAN (President Substitute) LESSONS LESSONS START https://corsi.unige.it/corsi/9008/studenti-orario Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION The exam consists in the development of a group project that demonstrates understanding of the course content and the ability to apply the acquired tools in a design context. ASSESSMENT METHODS The evaluation is based on the assessment of: Knowledge of key concepts Critical analysis skills FURTHER INFORMATION Students with disabilities or learning disorders are allowed to use specific modalities and supports that will be determined on a case-by-case basis in agreement with the Delegate of the Engineering courses in the Committee for the Inclusion of Students with Disabilities. Students are invited to contact the teacher of this course and copy the Delegate (https://unige.it/commissioni/comitatoperlinclusionedeglistudenticondisabilita.html). Agenda 2030 - Sustainable Development Goals Quality education Gender equality