AISA in a Nutshell
Artificial Intelligence (AI) intrinsically requires dedicated software and the related software engineering (SE) skills. Additionally, profound domain knowledge (X) in engineering, sciences and didactics are usually needed in order to efficiently and effectively use AI in academia and industry. AISA aims at educating specialists that are equipped with interdisciplinary skills in all contributing disciplines: AI+SE+X.
AI+SE+X: AISA's paradigm
Artificial Intelligence (AI) is a key technology in today's industrial and academic life. It comprises a huge variety of different methods, tools, and use cases. Understanding the relation between domain specific problems and the proper AI tools to be used is a key competence that is often lacking. Also, the development of you AI methodologies requires profound knowledge.
Software Engineering (SE) is a competence of neglected in academia. When developing research codes, sophisticated individual AI solutions, or simulation tools, things like documentation, testing, code readability, robustness, and so forth are often neglected. However, SE skills can boost efficiency in this regard. They can offer many benefits in larger teams, and for community wide roll out of academic and industrial solutions, and they improve on the sustainability of sodtware and the related methods.
Application domains (X) come along with specific requirements. For instance, basic physical principles must be obeyed. Nolet about the data may be available. Side conditions not captured in the data such as experimental conditions may be relevant. Result representation can be critical in order to trigger acceptance. Interaction with domain specific research data infrastructure may be required.
By fusing competences from AI, SE and X, AISA will equip specialists with the needed tools, methods, workflows, and didactic skills in order to trigger acceptance of novel technology. This is our vision.