Desafíos actuales de la Inteligencia Artificial

210 Desafíos actuales de la Inteligencia Artificial Looking forward, several areas warrant further research to advance the understanding and application of AI visualization. There is a need for ongoing refinement and enhance- ment of visualization tools such as SusAD. Future research should focus on developing more sophisticated methodologies for capturing and representing the complex interactions and effects of AI systems. Empirical validation is also crucial; conducting real-world case studies across different industries and public sectors will provide insights into the practical applica- tions of the SusAD framework and identify potential improvements. Furthermore, exploring additional metrics and dimensions for inclusion in visualization frameworks will contribute to a more comprehensive understanding of AI impacts. This ex- ploration should delve deeper into social, ethical, and environmental aspects. Additionally, future research should examine how visualization tools can be integrated with other deci- sion-support systems and frameworks, including risk assessment models, compliance moni- toring systems, and strategic planning tools. Engaging diverse stakeholders in the development and use of visualization tools is also vital. Research should focus on understanding the needs and perspectives of various user groups to better tailor tools to their requirements. Lastly, investigating the long-term impacts of AI technologies using visualization tools is important for understanding how AI evolves over time and its subsequent effects on organizational and societal outcomes. By addressing these research areas, future studies can contribute to more effective and comprehensive approaches for managing AI technologies, ultimately supporting their ethical and sustainable deployment. 5. REFERENCES ALMGREN, R. and SKOBELEV, D., 2020. Evolution of Technology and Technology Governance. Journal of Open Innovation: Technology, Market, and Complexity , vol. 6, no. 2, ISSN 2199-8531. DOI 10.3390/joitmc6020022. BANKINS, S. and FORMOSA, P., 2023. The Ethical Implications of Artificial Intelli- gence (AI) For Meaningful Work. Journal of Business Ethics , vol. 185, no. 4, ISSN 1573-0697. DOI 10.1007/s10551-023-05339-7. BEAUXIS-AUSSALET, E., BEHRISCH, M., BORGO, R., CHAU, D.H., COLLINS, C., EBERT, D., EL-ASSADY, M., ENDERT, A., KEIM, D.A., KOHLHAMMER, J., OEL- KE, D., PELTONEN, J., RIVEIRO, M., SCHRECK, T., STROBELT, H. and VAN WIJK, J.J., 2021. The Role of Interactive Visualization in Fostering Trust in AI. IEEE Computer Graphics and Applications , vol. 41, no. 6, ISSN 1558-1756. DOI 10.1109/MCG.2021.3107875. CHATZIMPARMPAS, A., MARTINS, R.M., JUSUFI, I., KUCHER, K., ROSSI, F. and KERREN, A., 2020. The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations. Computer Graphics Forum , vol. 39, no. 3, ISSN 1467- 8659. DOI 10.1111/cgf.14034.